From 5ed31e9117d6bff7c14a2d19db03c71846b0690d Mon Sep 17 00:00:00 2001 From: SOMANSHU AGARWAL Date: Thu, 5 Sep 2019 13:02:33 -0400 Subject: [PATCH 01/28] Part 1.2 change in kernel.cu --- src/kernel.cu | 36 +++++++++++++++++++++++++++++++++++- 1 file changed, 35 insertions(+), 1 deletion(-) diff --git a/src/kernel.cu b/src/kernel.cu index 74dffcb..ea2e65c 100644 --- a/src/kernel.cu +++ b/src/kernel.cu @@ -233,7 +233,38 @@ __device__ glm::vec3 computeVelocityChange(int N, int iSelf, const glm::vec3 *po // Rule 1: boids fly towards their local perceived center of mass, which excludes themselves // Rule 2: boids try to stay a distance d away from each other // Rule 3: boids try to match the speed of surrounding boids - return glm::vec3(0.0f, 0.0f, 0.0f); + glm::vec3 updatedVel(0.0f, 0.0f, 0.0f); + + // Rule 1 + glm::vec3 vectPerceived(0.0f, 0.0f, 0.0f); + for (int i =0, i< N ; i++) { + float dist = sqrt(pow(pos[iSelf].x - pos[i].x) + pow(pos[iSelf].y - pos[i].y) + pow(pos[iSelf].z - pos[i].z)); + if (iSelf!=i && dist < rule1Distance) + vectPerceived += pos[i]; + } + vectPerceived = vectPerceived/N-1; + updatedVel = updatedVel + (vectPerceived - pos[iSelf])*rule1Scale; + + // Rule 2 + glm::vec3 vectC(0.0f, 0.0f, 0.0f); + for (int i =0, i< N ; i++) { + float dist = sqrt(pow(pos[iSelf].x - pos[i].x) + pow(pos[iSelf].y - pos[i].y) + pow(pos[iSelf].z - pos[i].z)); + if (iSelf!=i && dist < rule2Distance) + vectC -= (pos[i] - pos[iSelf]); + } + updatedVel += vectC*rule2Scale; + + // Rule 3 + glm::vec3 vectPerceviedVel(0.0f, 0.0f, 0.0f); + for (int i =0, i< N ; i++) { + float dist = sqrt(pow(pos[iSelf].x - pos[i].x) + pow(pos[iSelf].y - pos[i].y) + pow(pos[iSelf].z - pos[i].z)); + if (iSelf!=i && dist < rule3Distance) + vectPerceivedVel += pos[i]; + } + vectPerceived = vectPerceived/N-1; + updatedVel = updatedVel + (vectPerceivedVel)*rule3Scale; + + return updatedVel; } /** @@ -245,6 +276,9 @@ __global__ void kernUpdateVelocityBruteForce(int N, glm::vec3 *pos, // Compute a new velocity based on pos and vel1 // Clamp the speed // Record the new velocity into vel2. Question: why NOT vel1? + int index = threadIdx; + glm::vec3 updateVel = computeVelocityChange(N, index, pos,vel); + vel2 = vel1 + updatedVel; } /** From 9eea6f63b4fea8e88b13acdd56429d04ca25c748 Mon Sep 17 00:00:00 2001 From: SOMANSHU AGARWAL Date: Thu, 5 Sep 2019 20:20:34 -0400 Subject: [PATCH 02/28] Further changes in the code for Part 1.2 --- src/kernel.cu | 40 +++++++++++++++++++++++++++------------- 1 file changed, 27 insertions(+), 13 deletions(-) diff --git a/src/kernel.cu b/src/kernel.cu index ea2e65c..4efe066 100644 --- a/src/kernel.cu +++ b/src/kernel.cu @@ -237,31 +237,31 @@ __device__ glm::vec3 computeVelocityChange(int N, int iSelf, const glm::vec3 *po // Rule 1 glm::vec3 vectPerceived(0.0f, 0.0f, 0.0f); - for (int i =0, i< N ; i++) { - float dist = sqrt(pow(pos[iSelf].x - pos[i].x) + pow(pos[iSelf].y - pos[i].y) + pow(pos[iSelf].z - pos[i].z)); + for (int i = 0; i < N; i++) { + float dist = sqrt(pow(pos[iSelf].x - pos[i].x,2) + pow(pos[iSelf].y - pos[i].y,2) + pow(pos[iSelf].z - pos[i].z,2)); if (iSelf!=i && dist < rule1Distance) vectPerceived += pos[i]; } - vectPerceived = vectPerceived/N-1; + vectPerceived /= N-1; updatedVel = updatedVel + (vectPerceived - pos[iSelf])*rule1Scale; // Rule 2 glm::vec3 vectC(0.0f, 0.0f, 0.0f); - for (int i =0, i< N ; i++) { - float dist = sqrt(pow(pos[iSelf].x - pos[i].x) + pow(pos[iSelf].y - pos[i].y) + pow(pos[iSelf].z - pos[i].z)); + for (int i = 0; i < N; i++) { + float dist = sqrt(pow(pos[iSelf].x - pos[i].x,2) + pow(pos[iSelf].y - pos[i].y,2) + pow(pos[iSelf].z - pos[i].z,2)); if (iSelf!=i && dist < rule2Distance) vectC -= (pos[i] - pos[iSelf]); } updatedVel += vectC*rule2Scale; - + printf("Here it came \n"); // Rule 3 - glm::vec3 vectPerceviedVel(0.0f, 0.0f, 0.0f); - for (int i =0, i< N ; i++) { - float dist = sqrt(pow(pos[iSelf].x - pos[i].x) + pow(pos[iSelf].y - pos[i].y) + pow(pos[iSelf].z - pos[i].z)); + glm::vec3 vectPerceivedVel(0.0f, 0.0f, 0.0f); + for (int i = 0; i < N; i++) { + float dist = sqrt(pow(pos[iSelf].x - pos[i].x,2) + pow(pos[iSelf].y - pos[i].y,2) + pow(pos[iSelf].z - pos[i].z,2)); if (iSelf!=i && dist < rule3Distance) vectPerceivedVel += pos[i]; } - vectPerceived = vectPerceived/N-1; + vectPerceivedVel /= N-1; updatedVel = updatedVel + (vectPerceivedVel)*rule3Scale; return updatedVel; @@ -276,9 +276,17 @@ __global__ void kernUpdateVelocityBruteForce(int N, glm::vec3 *pos, // Compute a new velocity based on pos and vel1 // Clamp the speed // Record the new velocity into vel2. Question: why NOT vel1? - int index = threadIdx; - glm::vec3 updateVel = computeVelocityChange(N, index, pos,vel); - vel2 = vel1 + updatedVel; + int index = threadIdx.x + (blockIdx.x * blockDim.x); + if (index > N) { + return; + } + glm::vec3 updatedVel{ computeVelocityChange(N, index, pos, vel1) }; + vel2[index] = vel1[index] + updatedVel; + //float length = glm::length(vel2[index]); + //if (length > maxSpeed) { + // vel2[index] = maxSpeed / length * vel2[index]; + //} + vel2[index] = glm::clamp(vel2[index], 0.0f, maxSpeed); } /** @@ -383,6 +391,12 @@ __global__ void kernUpdateVelNeighborSearchCoherent( void Boids::stepSimulationNaive(float dt) { // TODO-1.2 - use the kernels you wrote to step the simulation forward in time. // TODO-1.2 ping-pong the velocity buffers + dim3 fullBlocksPerGrid((numObjects + blockSize - 1) / blockSize); + kernUpdateVelocityBruteForce << > > (numObjects,dev_pos,dev_vel1,dev_vel2); + checkCUDAErrorWithLine("brute force failed"); + kernUpdatePos << > > (numObjects,dt,dev_pos,dev_vel2); + checkCUDAErrorWithLine("update Position Function Failed"); + dev_vel1 = dev_vel2; } void Boids::stepSimulationScatteredGrid(float dt) { From c4eb39dcef9a8870d70f5011f1338ff57233d6f3 Mon Sep 17 00:00:00 2001 From: SOMANSHU AGARWAL Date: Fri, 6 Sep 2019 02:41:01 -0400 Subject: [PATCH 03/28] Changes for Part 2.1 added --- src/kernel.cu | 171 ++++++++++++++++++++++++++++++++++++++++++++++---- src/main.cpp | 2 +- 2 files changed, 159 insertions(+), 14 deletions(-) diff --git a/src/kernel.cu b/src/kernel.cu index 4efe066..1c60232 100644 --- a/src/kernel.cu +++ b/src/kernel.cu @@ -165,10 +165,25 @@ void Boids::initSimulation(int N) { gridInverseCellWidth = 1.0f / gridCellWidth; float halfGridWidth = gridCellWidth * halfSideCount; gridMinimum.x -= halfGridWidth; - gridMinimum.y -= halfGridWidth; + gridMinimum.y -= halfGridWidth; gridMinimum.z -= halfGridWidth; // TODO-2.1 TODO-2.3 - Allocate additional buffers here. + cudaMalloc((void**)&dev_particleArrayIndices, N * sizeof(int)); + checkCUDAErrorWithLine("cudaMalloc dev_particleArrayIndices failed!"); + + cudaMalloc((void**)&dev_particleGridIndices, N * sizeof(int)); + checkCUDAErrorWithLine("cudaMalloc dev_particleGridIndices failed!"); + + cudaMalloc((void**)&dev_gridCellStartIndices, N * sizeof(int)); + checkCUDAErrorWithLine("cudaMalloc dev_gridCellStartIndices failed!"); + + cudaMalloc((void**)&dev_gridCellEndIndices, N * sizeof(int)); + checkCUDAErrorWithLine("cudaMalloc dev_gridCellEndIndices failed!"); + + dev_thrust_particleArrayIndices = thrust::device_ptr(dev_particleArrayIndices); + dev_thrust_particleGridIndices = thrust::device_ptr(dev_particleGridIndices); + cudaDeviceSynchronize(); } @@ -237,33 +252,43 @@ __device__ glm::vec3 computeVelocityChange(int N, int iSelf, const glm::vec3 *po // Rule 1 glm::vec3 vectPerceived(0.0f, 0.0f, 0.0f); + int numberNeighbours = 0; for (int i = 0; i < N; i++) { float dist = sqrt(pow(pos[iSelf].x - pos[i].x,2) + pow(pos[iSelf].y - pos[i].y,2) + pow(pos[iSelf].z - pos[i].z,2)); - if (iSelf!=i && dist < rule1Distance) - vectPerceived += pos[i]; + if (iSelf != i && dist < rule1Distance) { + vectPerceived += pos[i]; + numberNeighbours++; + } } - vectPerceived /= N-1; - updatedVel = updatedVel + (vectPerceived - pos[iSelf])*rule1Scale; + if (numberNeighbours) { + vectPerceived /= numberNeighbours; + updatedVel = updatedVel + (vectPerceived - pos[iSelf])*rule1Scale; + } // Rule 2 glm::vec3 vectC(0.0f, 0.0f, 0.0f); for (int i = 0; i < N; i++) { float dist = sqrt(pow(pos[iSelf].x - pos[i].x,2) + pow(pos[iSelf].y - pos[i].y,2) + pow(pos[iSelf].z - pos[i].z,2)); - if (iSelf!=i && dist < rule2Distance) - vectC -= (pos[i] - pos[iSelf]); + if (iSelf != i && dist < rule2Distance) { + vectC -= (pos[i] - pos[iSelf]); + } } updatedVel += vectC*rule2Scale; printf("Here it came \n"); // Rule 3 glm::vec3 vectPerceivedVel(0.0f, 0.0f, 0.0f); + numberNeighbours = 0; for (int i = 0; i < N; i++) { float dist = sqrt(pow(pos[iSelf].x - pos[i].x,2) + pow(pos[iSelf].y - pos[i].y,2) + pow(pos[iSelf].z - pos[i].z,2)); - if (iSelf!=i && dist < rule3Distance) - vectPerceivedVel += pos[i]; + if (iSelf != i && dist < rule3Distance) { + vectPerceivedVel += vel[i]; + numberNeighbours++; + } } - vectPerceivedVel /= N-1; - updatedVel = updatedVel + (vectPerceivedVel)*rule3Scale; - + if (numberNeighbours) { + vectPerceivedVel /= numberNeighbours; + updatedVel = updatedVel + (vectPerceivedVel)*rule3Scale; + } return updatedVel; } @@ -277,7 +302,7 @@ __global__ void kernUpdateVelocityBruteForce(int N, glm::vec3 *pos, // Clamp the speed // Record the new velocity into vel2. Question: why NOT vel1? int index = threadIdx.x + (blockIdx.x * blockDim.x); - if (index > N) { + if (index >= N) { return; } glm::vec3 updatedVel{ computeVelocityChange(N, index, pos, vel1) }; @@ -331,6 +356,14 @@ __global__ void kernComputeIndices(int N, int gridResolution, // - Label each boid with the index of its grid cell. // - Set up a parallel array of integer indices as pointers to the actual // boid data in pos and vel1/vel2 + int index = threadIdx.x + blockIdx.x * blockDim.x; + if (index >= N) + return; + + indices[index] = index; + glm::vec3 gridCoord = glm::floor((pos[index] - gridMin) * inverseCellWidth); + int index1D = gridIndex3Dto1D(gridCoord.x, gridCoord.y, gridCoord.z, gridResolution); + gridIndices[index] = index1D; } // LOOK-2.1 Consider how this could be useful for indicating that a cell @@ -348,6 +381,18 @@ __global__ void kernIdentifyCellStartEnd(int N, int *particleGridIndices, // Identify the start point of each cell in the gridIndices array. // This is basically a parallel unrolling of a loop that goes // "this index doesn't match the one before it, must be a new cell!" + int index = threadIdx.x + blockIdx.x * blockDim.x; + if (index >= N) + return; + + if (index == 0) + gridCellStartIndices[particleGridIndices[index]] = 0; + + else if (particleGridIndices[index - 1] != particleGridIndices[index]) { + gridCellStartIndices[particleGridIndices[index]] = index; + gridCellEndIndices[particleGridIndices[index-1]] = index-1; + } + } __global__ void kernUpdateVelNeighborSearchScattered( @@ -364,6 +409,77 @@ __global__ void kernUpdateVelNeighborSearchScattered( // - Access each boid in the cell and compute velocity change from // the boids rules, if this boid is within the neighborhood distance. // - Clamp the speed change before putting the new speed in vel2 + + int index = threadIdx.x + blockIdx.x * blockDim.x; + if (index >= N) + return; + + glm::vec3 vectPerceived(0.0f, 0.0f, 0.0f); + glm::vec3 vectC(0.0f, 0.0f, 0.0f); + glm::vec3 vectPerceivedVel(0.0f, 0.0f, 0.0f); + glm::vec3 vectVelChange(0.0f, 0.0f, 0.0f); + + glm::vec3 boidCoord = glm::floor((pos[index] - gridMin) * inverseCellWidth); + int boidGridId = gridIndex3Dto1D(boidCoord.x, boidCoord.y, boidCoord.z, gridResolution); + + int candidateGridId,boidStart,boidEnd,numberNeighboursRule1 = 0,numberNeighboursRule3 = 0; + + for (int x = boidCoord.x - 1; x <= boidCoord.x + 1; x++) { + if (x < 0 || x >= gridResolution) + continue; + for (int y = boidCoord.y - 1; y <= boidCoord.y; y++) { + if (y < 0 || y >= gridResolution) + continue; + for (int z = boidCoord.z - 1; z <= boidCoord.z; z++) { + if (z < 0 || z >= gridResolution) + continue; + + candidateGridId = gridIndex3Dto1D(boidCoord.x, boidCoord.y, boidCoord.z, gridResolution); + boidStart = gridCellStartIndices[candidateGridId]; + boidEnd = gridCellEndIndices[candidateGridId]; + if (boidStart == -1 || boidEnd == -1) + continue; + for (int id = boidStart ; id<= boidEnd ; id++) { + int boidCheckId = particleArrayIndices[id]; + + // Rule 1 + if (index != boidCheckId && glm::distance(pos[boidCheckId], pos[index]) < rule1Distance) { + vectPerceived += pos[boidCheckId]; + numberNeighboursRule1++; + } + + // Rule 2 + if (index != boidCheckId && glm::distance(pos[boidCheckId], pos[index]) < rule2Distance) { + vectC -= (pos[boidCheckId] - pos[index]); + } + + // Rule 3 + if (index != boidCheckId && glm::distance(pos[boidCheckId], pos[index]) < rule3Distance) { + vectPerceivedVel += vel1[boidCheckId]; + numberNeighboursRule3++; + } + } + } + } + } + + vel2 = vel1; + if (numberNeighboursRule1) { + vectPerceived /= numberNeighboursRule1; + vectVelChange = (vectPerceived - pos[index])*rule1Scale; + } + + vectVelChange = vectVelChange + vectC; + + if (numberNeighboursRule3) { + vectPerceivedVel /= numberNeighboursRule3; + vectVelChange += vectPerceivedVel*rule3Scale; + } + + vel2[index] = vel1[index] + vectVelChange; + vel2[index] = glm::clamp(vel2[index],0.0f, maxSpeed); + //vel2[index] = vel1[index] + vectVelChange; + } __global__ void kernUpdateVelNeighborSearchCoherent( @@ -412,6 +528,29 @@ void Boids::stepSimulationScatteredGrid(float dt) { // - Perform velocity updates using neighbor search // - Update positions // - Ping-pong buffers as needed + + dim3 fullBlocksPerGrid((numObjects + blockSize - 1) / blockSize); + + kernResetIntBuffer << > > (numObjects, dev_gridCellStartIndices,-1); + checkCUDAErrorWithLine("resetting dev_gridCellStartIndices failed "); + kernResetIntBuffer << > > (numObjects, dev_gridCellEndIndices, -1); + checkCUDAErrorWithLine("resetting dev_gridCellEndIndices failed "); + + kernComputeIndices << > > (numObjects,gridSideCount,gridMinimum,gridInverseCellWidth,dev_pos, dev_particleArrayIndices, dev_particleGridIndices); + checkCUDAErrorWithLine("Computing indices failed "); + + thrust::sort_by_key(dev_thrust_particleGridIndices, dev_thrust_particleGridIndices + numObjects, dev_thrust_particleArrayIndices); + + kernIdentifyCellStartEnd << > > (numObjects, dev_particleGridIndices, dev_gridCellStartIndices, dev_gridCellEndIndices); + checkCUDAErrorWithLine("Identifying Start and End Boid Points failed "); + + kernUpdateVelNeighborSearchScattered << > > (numObjects,gridSideCount,gridMinimum,gridInverseCellWidth, gridCellWidth, dev_gridCellStartIndices, dev_gridCellEndIndices, dev_particleArrayIndices,dev_pos,dev_vel1,dev_vel2); + checkCUDAErrorWithLine("Identifying Start and End Boid Points failed "); + + kernUpdatePos << > > (numObjects, dt, dev_pos, dev_vel2); + checkCUDAErrorWithLine("update Position Function Failed"); + + dev_vel1 = dev_vel2; } void Boids::stepSimulationCoherentGrid(float dt) { @@ -438,6 +577,12 @@ void Boids::endSimulation() { cudaFree(dev_pos); // TODO-2.1 TODO-2.3 - Free any additional buffers here. + + cudaFree(dev_particleArrayIndices); + cudaFree(dev_particleGridIndices); + cudaFree(dev_gridCellStartIndices); + cudaFree(dev_gridCellEndIndices); + } void Boids::unitTest() { diff --git a/src/main.cpp b/src/main.cpp index b82c8c6..063a977 100644 --- a/src/main.cpp +++ b/src/main.cpp @@ -14,7 +14,7 @@ // LOOK-2.1 LOOK-2.3 - toggles for UNIFORM_GRID and COHERENT_GRID #define VISUALIZE 1 -#define UNIFORM_GRID 0 +#define UNIFORM_GRID 1 #define COHERENT_GRID 0 // LOOK-1.2 - change this to adjust particle count in the simulation From 188396461181d733144519c7abbe4c32f8ac754a Mon Sep 17 00:00:00 2001 From: SOMANSHU AGARWAL Date: Sat, 7 Sep 2019 00:34:20 -0400 Subject: [PATCH 04/28] New Changes --- src/kernel.cu | 81 ++++++++++++++++++++++++++++++--------------------- 1 file changed, 48 insertions(+), 33 deletions(-) diff --git a/src/kernel.cu b/src/kernel.cu index 1c60232..2b2c98b 100644 --- a/src/kernel.cu +++ b/src/kernel.cu @@ -175,14 +175,14 @@ void Boids::initSimulation(int N) { cudaMalloc((void**)&dev_particleGridIndices, N * sizeof(int)); checkCUDAErrorWithLine("cudaMalloc dev_particleGridIndices failed!"); - cudaMalloc((void**)&dev_gridCellStartIndices, N * sizeof(int)); + cudaMalloc((void**)&dev_gridCellStartIndices, gridCellCount * sizeof(int)); checkCUDAErrorWithLine("cudaMalloc dev_gridCellStartIndices failed!"); - cudaMalloc((void**)&dev_gridCellEndIndices, N * sizeof(int)); + cudaMalloc((void**)&dev_gridCellEndIndices, gridCellCount * sizeof(int)); checkCUDAErrorWithLine("cudaMalloc dev_gridCellEndIndices failed!"); - dev_thrust_particleArrayIndices = thrust::device_ptr(dev_particleArrayIndices); - dev_thrust_particleGridIndices = thrust::device_ptr(dev_particleGridIndices); + dev_thrust_particleArrayIndices = thrust::device_pointer_cast(dev_particleArrayIndices); + dev_thrust_particleGridIndices = thrust::device_pointer_cast(dev_particleGridIndices); cudaDeviceSynchronize(); } @@ -254,8 +254,8 @@ __device__ glm::vec3 computeVelocityChange(int N, int iSelf, const glm::vec3 *po glm::vec3 vectPerceived(0.0f, 0.0f, 0.0f); int numberNeighbours = 0; for (int i = 0; i < N; i++) { - float dist = sqrt(pow(pos[iSelf].x - pos[i].x,2) + pow(pos[iSelf].y - pos[i].y,2) + pow(pos[iSelf].z - pos[i].z,2)); - if (iSelf != i && dist < rule1Distance) { + //float dist = sqrt(pow(pos[iSelf].x - pos[i].x,2) + pow(pos[iSelf].y - pos[i].y,2) + pow(pos[iSelf].z - pos[i].z,2)); + if (iSelf != i && glm::distance(pos[iSelf], pos[i]) < rule1Distance) { vectPerceived += pos[i]; numberNeighbours++; } @@ -268,19 +268,19 @@ __device__ glm::vec3 computeVelocityChange(int N, int iSelf, const glm::vec3 *po // Rule 2 glm::vec3 vectC(0.0f, 0.0f, 0.0f); for (int i = 0; i < N; i++) { - float dist = sqrt(pow(pos[iSelf].x - pos[i].x,2) + pow(pos[iSelf].y - pos[i].y,2) + pow(pos[iSelf].z - pos[i].z,2)); - if (iSelf != i && dist < rule2Distance) { + //float dist = sqrt(pow(pos[iSelf].x - pos[i].x,2) + pow(pos[iSelf].y - pos[i].y,2) + pow(pos[iSelf].z - pos[i].z,2)); + if (iSelf != i && glm::distance(pos[iSelf], pos[i]) < rule2Distance) { vectC -= (pos[i] - pos[iSelf]); } } updatedVel += vectC*rule2Scale; - printf("Here it came \n"); + //printf("Here it came \n"); // Rule 3 glm::vec3 vectPerceivedVel(0.0f, 0.0f, 0.0f); numberNeighbours = 0; for (int i = 0; i < N; i++) { - float dist = sqrt(pow(pos[iSelf].x - pos[i].x,2) + pow(pos[iSelf].y - pos[i].y,2) + pow(pos[iSelf].z - pos[i].z,2)); - if (iSelf != i && dist < rule3Distance) { + //float dist = sqrt(pow(pos[iSelf].x - pos[i].x,2) + pow(pos[iSelf].y - pos[i].y,2) + pow(pos[iSelf].z - pos[i].z,2)); + if (iSelf != i && glm::distance(pos[iSelf], pos[i]) < rule3Distance) { vectPerceivedVel += vel[i]; numberNeighbours++; } @@ -311,7 +311,7 @@ __global__ void kernUpdateVelocityBruteForce(int N, glm::vec3 *pos, //if (length > maxSpeed) { // vel2[index] = maxSpeed / length * vel2[index]; //} - vel2[index] = glm::clamp(vel2[index], 0.0f, maxSpeed); + vel2[index] = glm::clamp(vel2[index], -maxSpeed, maxSpeed); } /** @@ -362,7 +362,8 @@ __global__ void kernComputeIndices(int N, int gridResolution, indices[index] = index; glm::vec3 gridCoord = glm::floor((pos[index] - gridMin) * inverseCellWidth); - int index1D = gridIndex3Dto1D(gridCoord.x, gridCoord.y, gridCoord.z, gridResolution); + int index1D = gridIndex3Dto1D((int) gridCoord.x, (int) gridCoord.y, (int) gridCoord.z, gridResolution); + //printf("Indices are: %d \n", index1D); gridIndices[index] = index1D; } @@ -388,6 +389,9 @@ __global__ void kernIdentifyCellStartEnd(int N, int *particleGridIndices, if (index == 0) gridCellStartIndices[particleGridIndices[index]] = 0; + else if (index == N-1) + gridCellEndIndices[particleGridIndices[index]] = N-1; + else if (particleGridIndices[index - 1] != particleGridIndices[index]) { gridCellStartIndices[particleGridIndices[index]] = index; gridCellEndIndices[particleGridIndices[index-1]] = index-1; @@ -410,6 +414,10 @@ __global__ void kernUpdateVelNeighborSearchScattered( // the boids rules, if this boid is within the neighborhood distance. // - Clamp the speed change before putting the new speed in vel2 + /*for (int i = 0; i < N; i++) { + printf("%d\n", particleArrayIndices[i]); + }*/ + int index = threadIdx.x + blockIdx.x * blockDim.x; if (index >= N) return; @@ -417,37 +425,42 @@ __global__ void kernUpdateVelNeighborSearchScattered( glm::vec3 vectPerceived(0.0f, 0.0f, 0.0f); glm::vec3 vectC(0.0f, 0.0f, 0.0f); glm::vec3 vectPerceivedVel(0.0f, 0.0f, 0.0f); - glm::vec3 vectVelChange(0.0f, 0.0f, 0.0f); - + glm::vec3 boidCoord = glm::floor((pos[index] - gridMin) * inverseCellWidth); - int boidGridId = gridIndex3Dto1D(boidCoord.x, boidCoord.y, boidCoord.z, gridResolution); - + //printf("Relative position after floor is : x: %0.2f , y: %0.2f, z: %0.2f \n", boidCoord.x, boidCoord.y, boidCoord.z); + //int boidGridId = gridIndex3Dto1D(boidCoord.x, boidCoord.y, boidCoord.z, gridResolution); + + int xStart = (int)boidCoord.x; + int yStart = (int)boidCoord.y; + int zStart = (int)boidCoord.z; + //int loopCount = 0; int candidateGridId,boidStart,boidEnd,numberNeighboursRule1 = 0,numberNeighboursRule3 = 0; - - for (int x = boidCoord.x - 1; x <= boidCoord.x + 1; x++) { + //printf("Boid Co-ordinate: x: %d ,y: %d, z:%d \n", boidCoord.x, boidCoord.y, boidCoord.z); + for (int x = xStart - 1; x <= xStart + 1; x++) { if (x < 0 || x >= gridResolution) continue; - for (int y = boidCoord.y - 1; y <= boidCoord.y; y++) { + for (int y = yStart - 1; y <= yStart + 1 ; y++) { if (y < 0 || y >= gridResolution) continue; - for (int z = boidCoord.z - 1; z <= boidCoord.z; z++) { + for (int z = zStart - 1; z <= zStart +1 ; z++) { if (z < 0 || z >= gridResolution) continue; - candidateGridId = gridIndex3Dto1D(boidCoord.x, boidCoord.y, boidCoord.z, gridResolution); + candidateGridId = gridIndex3Dto1D(x,y,z, gridResolution); boidStart = gridCellStartIndices[candidateGridId]; boidEnd = gridCellEndIndices[candidateGridId]; + //printf("Boid Start: %d and Boid End: %d \n", boidStart, boidEnd); if (boidStart == -1 || boidEnd == -1) continue; for (int id = boidStart ; id<= boidEnd ; id++) { int boidCheckId = particleArrayIndices[id]; - + //loopCount++; // Rule 1 if (index != boidCheckId && glm::distance(pos[boidCheckId], pos[index]) < rule1Distance) { vectPerceived += pos[boidCheckId]; numberNeighboursRule1++; } - + // glm::distance(pos[boidCheckId], pos[index]) // Rule 2 if (index != boidCheckId && glm::distance(pos[boidCheckId], pos[index]) < rule2Distance) { vectC -= (pos[boidCheckId] - pos[index]); @@ -462,22 +475,22 @@ __global__ void kernUpdateVelNeighborSearchScattered( } } } - - vel2 = vel1; + //printf("Loop Count : %d\n", loopCount); + if (numberNeighboursRule1) { vectPerceived /= numberNeighboursRule1; - vectVelChange = (vectPerceived - pos[index])*rule1Scale; + vectPerceived = (vectPerceived - pos[index])*rule1Scale; } - vectVelChange = vectVelChange + vectC; + vectC = vectC*rule2Scale; if (numberNeighboursRule3) { vectPerceivedVel /= numberNeighboursRule3; - vectVelChange += vectPerceivedVel*rule3Scale; + vectPerceivedVel = vectPerceivedVel*rule3Scale; } - vel2[index] = vel1[index] + vectVelChange; - vel2[index] = glm::clamp(vel2[index],0.0f, maxSpeed); + vel2[index] = vel1[index] + vectPerceived + vectC + vectPerceivedVel; + vel2[index] = glm::clamp(vel2[index],-maxSpeed, maxSpeed); //vel2[index] = vel1[index] + vectVelChange; } @@ -530,10 +543,12 @@ void Boids::stepSimulationScatteredGrid(float dt) { // - Ping-pong buffers as needed dim3 fullBlocksPerGrid((numObjects + blockSize - 1) / blockSize); + dim3 gridResetSize((gridCellCount + blockSize - 1) / blockSize); - kernResetIntBuffer << > > (numObjects, dev_gridCellStartIndices,-1); + kernResetIntBuffer << > > (gridCellCount, dev_gridCellStartIndices,-1); checkCUDAErrorWithLine("resetting dev_gridCellStartIndices failed "); - kernResetIntBuffer << > > (numObjects, dev_gridCellEndIndices, -1); + + kernResetIntBuffer << > > (gridCellCount, dev_gridCellEndIndices, -1); checkCUDAErrorWithLine("resetting dev_gridCellEndIndices failed "); kernComputeIndices << > > (numObjects,gridSideCount,gridMinimum,gridInverseCellWidth,dev_pos, dev_particleArrayIndices, dev_particleGridIndices); From 0a10527158add8d05732903773e32321e79a62e1 Mon Sep 17 00:00:00 2001 From: SOMANSHU AGARWAL Date: Sat, 7 Sep 2019 02:44:32 -0400 Subject: [PATCH 05/28] Changes for Part 2.3 --- src/kernel.cu | 147 +++++++++++++++++++++++++++++++++++++++++++++++++- src/main.cpp | 2 +- 2 files changed, 147 insertions(+), 2 deletions(-) diff --git a/src/kernel.cu b/src/kernel.cu index 2b2c98b..c2b0676 100644 --- a/src/kernel.cu +++ b/src/kernel.cu @@ -85,6 +85,8 @@ int *dev_gridCellEndIndices; // to this cell? // TODO-2.3 - consider what additional buffers you might need to reshuffle // the position and velocity data to be coherent within cells. +glm::vec3 *dev_posCoherent; +glm::vec3 *dev_velCoherent; // LOOK-2.1 - Grid parameters based on simulation parameters. // These are automatically computed for you in Boids::initSimulation @@ -184,6 +186,12 @@ void Boids::initSimulation(int N) { dev_thrust_particleArrayIndices = thrust::device_pointer_cast(dev_particleArrayIndices); dev_thrust_particleGridIndices = thrust::device_pointer_cast(dev_particleGridIndices); + cudaMalloc((void**)&dev_posCoherent, N * sizeof(glm::vec3)); + checkCUDAErrorWithLine("cudaMalloc dev_gridCellEndIndices failed!"); + + cudaMalloc((void**)&dev_velCoherent, N * sizeof(glm::vec3)); + checkCUDAErrorWithLine("cudaMalloc dev_gridCellEndIndices failed!"); + cudaDeviceSynchronize(); } @@ -399,6 +407,34 @@ __global__ void kernIdentifyCellStartEnd(int N, int *particleGridIndices, } +// New function for rehuffling the boid data for contiguos allocation for boids within the cell + +__global__ void kernReshuffleBoidDataForCoherentSearch( + int N, int *particleArrayIndices, + glm::vec3 *pos, glm::vec3 *vel, + glm::vec3 *posShuffled, glm::vec3 *velShuffled) { + // Reshuffle pos and vel for continoug memeory access + + int index = threadIdx.x + blockIdx.x * blockDim.x; + if (index >= N) + return; + + posShuffled[index] = pos[particleArrayIndices[index]]; + velShuffled[index] = vel[particleArrayIndices[index]]; +} + +__global__ void kernUnshuffleBoidVelocityData( + int N, int *particleArrayIndices, + glm::vec3 *velShuffled, glm::vec3 *velUnshuffled) { + // Reshuffle pos and vel for continoug memeory access + + int index = threadIdx.x + blockIdx.x * blockDim.x; + if (index >= N) + return; + + velUnshuffled[particleArrayIndices[index]] = velShuffled[index]; +} + __global__ void kernUpdateVelNeighborSearchScattered( int N, int gridResolution, glm::vec3 gridMin, float inverseCellWidth, float cellWidth, @@ -512,6 +548,81 @@ __global__ void kernUpdateVelNeighborSearchCoherent( // - Access each boid in the cell and compute velocity change from // the boids rules, if this boid is within the neighborhood distance. // - Clamp the speed change before putting the new speed in vel2 + + int index = threadIdx.x + blockIdx.x * blockDim.x; + if (index >= N) + return; + + glm::vec3 vectPerceived(0.0f, 0.0f, 0.0f); + glm::vec3 vectC(0.0f, 0.0f, 0.0f); + glm::vec3 vectPerceivedVel(0.0f, 0.0f, 0.0f); + + glm::vec3 boidCoord = glm::floor((pos[index] - gridMin) * inverseCellWidth); + //printf("Relative position after floor is : x: %0.2f , y: %0.2f, z: %0.2f \n", boidCoord.x, boidCoord.y, boidCoord.z); + //int boidGridId = gridIndex3Dto1D(boidCoord.x, boidCoord.y, boidCoord.z, gridResolution); + + int xStart = (int)boidCoord.x; + int yStart = (int)boidCoord.y; + int zStart = (int)boidCoord.z; + //int loopCount = 0; + int candidateGridId, boidStart, boidEnd, numberNeighboursRule1 = 0, numberNeighboursRule3 = 0; + //printf("Boid Co-ordinate: x: %d ,y: %d, z:%d \n", boidCoord.x, boidCoord.y, boidCoord.z); + for (int x = xStart - 1; x <= xStart + 1; x++) { + if (x < 0 || x >= gridResolution) + continue; + for (int y = yStart - 1; y <= yStart + 1; y++) { + if (y < 0 || y >= gridResolution) + continue; + for (int z = zStart - 1; z <= zStart + 1; z++) { + if (z < 0 || z >= gridResolution) + continue; + + candidateGridId = gridIndex3Dto1D(x, y, z, gridResolution); + boidStart = gridCellStartIndices[candidateGridId]; + boidEnd = gridCellEndIndices[candidateGridId]; + //printf("Boid Start: %d and Boid End: %d \n", boidStart, boidEnd); + if (boidStart == -1 || boidEnd == -1) + continue; + for (int id = boidStart; id <= boidEnd; id++) { + //loopCount++; + // Rule 1 + if (index != id && glm::distance(pos[id], pos[index]) < rule1Distance) { + vectPerceived += pos[id]; + numberNeighboursRule1++; + } + // glm::distance(pos[boidCheckId], pos[index]) + // Rule 2 + if (index != id && glm::distance(pos[id], pos[index]) < rule2Distance) { + vectC -= (pos[id] - pos[index]); + } + + // Rule 3 + if (index != id && glm::distance(pos[id], pos[index]) < rule3Distance) { + vectPerceivedVel += vel1[id]; + numberNeighboursRule3++; + } + } + } + } + } + //printf("Loop Count : %d\n", loopCount); + + if (numberNeighboursRule1) { + vectPerceived /= numberNeighboursRule1; + vectPerceived = (vectPerceived - pos[index])*rule1Scale; + } + + vectC = vectC * rule2Scale; + + if (numberNeighboursRule3) { + vectPerceivedVel /= numberNeighboursRule3; + vectPerceivedVel = vectPerceivedVel * rule3Scale; + } + + vel2[index] = vel1[index] + vectPerceived + vectC + vectPerceivedVel; + vel2[index] = glm::clamp(vel2[index], -maxSpeed, maxSpeed); + //vel2[index] = vel1[index] + vectVelChange; + } /** @@ -560,7 +671,7 @@ void Boids::stepSimulationScatteredGrid(float dt) { checkCUDAErrorWithLine("Identifying Start and End Boid Points failed "); kernUpdateVelNeighborSearchScattered << > > (numObjects,gridSideCount,gridMinimum,gridInverseCellWidth, gridCellWidth, dev_gridCellStartIndices, dev_gridCellEndIndices, dev_particleArrayIndices,dev_pos,dev_vel1,dev_vel2); - checkCUDAErrorWithLine("Identifying Start and End Boid Points failed "); + checkCUDAErrorWithLine("Scattered Neighbour Search failed "); kernUpdatePos << > > (numObjects, dt, dev_pos, dev_vel2); checkCUDAErrorWithLine("update Position Function Failed"); @@ -584,6 +695,38 @@ void Boids::stepSimulationCoherentGrid(float dt) { // - Perform velocity updates using neighbor search // - Update positions // - Ping-pong buffers as needed. THIS MAY BE DIFFERENT FROM BEFORE. + + + dim3 fullBlocksPerGrid((numObjects + blockSize - 1) / blockSize); + dim3 gridResetSize((gridCellCount + blockSize - 1) / blockSize); + + kernResetIntBuffer << > > (gridCellCount, dev_gridCellStartIndices, -1); + checkCUDAErrorWithLine("resetting dev_gridCellStartIndices failed "); + + kernResetIntBuffer << > > (gridCellCount, dev_gridCellEndIndices, -1); + checkCUDAErrorWithLine("resetting dev_gridCellEndIndices failed "); + + kernComputeIndices << > > (numObjects, gridSideCount, gridMinimum, gridInverseCellWidth, dev_pos, dev_particleArrayIndices, dev_particleGridIndices); + checkCUDAErrorWithLine("Computing indices failed "); + + thrust::sort_by_key(dev_thrust_particleGridIndices, dev_thrust_particleGridIndices + numObjects, dev_thrust_particleArrayIndices); + + kernIdentifyCellStartEnd << > > (numObjects, dev_particleGridIndices, dev_gridCellStartIndices, dev_gridCellEndIndices); + checkCUDAErrorWithLine("Identifying Start and End Boid Points failed "); + + kernReshuffleBoidDataForCoherentSearch << > > (numObjects, dev_particleArrayIndices,dev_pos,dev_vel1,dev_posCoherent,dev_velCoherent); + checkCUDAErrorWithLine("Shuffling Boid pos and vel data for Coherent Search failed "); + + kernUpdateVelNeighborSearchCoherent << > > (numObjects, gridSideCount, gridMinimum, gridInverseCellWidth, gridCellWidth, dev_gridCellStartIndices, dev_gridCellEndIndices, dev_posCoherent, dev_velCoherent, dev_vel2); + checkCUDAErrorWithLine("Coherent Neighbour search failed "); + + kernUnshuffleBoidVelocityData << > > (numObjects, dev_particleArrayIndices,dev_vel2, dev_vel1); + checkCUDAErrorWithLine("Unshuffling velocity boid data failed failed "); + + kernUpdatePos << > > (numObjects, dt, dev_pos, dev_vel1); + checkCUDAErrorWithLine("update Position Function Failed"); + + //dev_vel1 = dev_velCoherent; } void Boids::endSimulation() { @@ -598,6 +741,8 @@ void Boids::endSimulation() { cudaFree(dev_gridCellStartIndices); cudaFree(dev_gridCellEndIndices); + cudaFree(dev_posCoherent); + cudaFree(dev_velCoherent); } void Boids::unitTest() { diff --git a/src/main.cpp b/src/main.cpp index 063a977..ddd0e3b 100644 --- a/src/main.cpp +++ b/src/main.cpp @@ -15,7 +15,7 @@ // LOOK-2.1 LOOK-2.3 - toggles for UNIFORM_GRID and COHERENT_GRID #define VISUALIZE 1 #define UNIFORM_GRID 1 -#define COHERENT_GRID 0 +#define COHERENT_GRID 1 // LOOK-1.2 - change this to adjust particle count in the simulation const int N_FOR_VIS = 5000; From 09388f84354afa869f2c13f1a221493dad1bd0e4 Mon Sep 17 00:00:00 2001 From: SOMANSHU AGARWAL Date: Sat, 7 Sep 2019 22:39:18 -0400 Subject: [PATCH 06/28] Final changes for Project 1 --- src/kernel.cu | 37 +++++++++++++++---------------------- src/main.cpp | 2 +- 2 files changed, 16 insertions(+), 23 deletions(-) diff --git a/src/kernel.cu b/src/kernel.cu index c2b0676..53df9f4 100644 --- a/src/kernel.cu +++ b/src/kernel.cu @@ -462,23 +462,19 @@ __global__ void kernUpdateVelNeighborSearchScattered( glm::vec3 vectC(0.0f, 0.0f, 0.0f); glm::vec3 vectPerceivedVel(0.0f, 0.0f, 0.0f); - glm::vec3 boidCoord = glm::floor((pos[index] - gridMin) * inverseCellWidth); - //printf("Relative position after floor is : x: %0.2f , y: %0.2f, z: %0.2f \n", boidCoord.x, boidCoord.y, boidCoord.z); - //int boidGridId = gridIndex3Dto1D(boidCoord.x, boidCoord.y, boidCoord.z, gridResolution); + float max_distance = max(rule1Distance, max(rule2Distance, rule3Distance)); + glm::ivec3 maxCellIndex = ((pos[index] - gridMin) + max_distance) * inverseCellWidth; + glm::ivec3 minCellIndex = ((pos[index] - gridMin) - max_distance) * inverseCellWidth; - int xStart = (int)boidCoord.x; - int yStart = (int)boidCoord.y; - int zStart = (int)boidCoord.z; - //int loopCount = 0; int candidateGridId,boidStart,boidEnd,numberNeighboursRule1 = 0,numberNeighboursRule3 = 0; //printf("Boid Co-ordinate: x: %d ,y: %d, z:%d \n", boidCoord.x, boidCoord.y, boidCoord.z); - for (int x = xStart - 1; x <= xStart + 1; x++) { + for (int x = minCellIndex.x; x <= maxCellIndex.x ; x++) { if (x < 0 || x >= gridResolution) continue; - for (int y = yStart - 1; y <= yStart + 1 ; y++) { + for (int y = minCellIndex.y; y <= maxCellIndex.y; y++) { if (y < 0 || y >= gridResolution) continue; - for (int z = zStart - 1; z <= zStart +1 ; z++) { + for (int z = minCellIndex.z; z <= maxCellIndex.z; z++) { if (z < 0 || z >= gridResolution) continue; @@ -557,26 +553,23 @@ __global__ void kernUpdateVelNeighborSearchCoherent( glm::vec3 vectC(0.0f, 0.0f, 0.0f); glm::vec3 vectPerceivedVel(0.0f, 0.0f, 0.0f); - glm::vec3 boidCoord = glm::floor((pos[index] - gridMin) * inverseCellWidth); - //printf("Relative position after floor is : x: %0.2f , y: %0.2f, z: %0.2f \n", boidCoord.x, boidCoord.y, boidCoord.z); - //int boidGridId = gridIndex3Dto1D(boidCoord.x, boidCoord.y, boidCoord.z, gridResolution); + float max_distance = max(rule1Distance, max(rule2Distance, rule3Distance)); + glm::ivec3 maxCellIndex = ((pos[index] - gridMin) + max_distance) * inverseCellWidth; + glm::ivec3 minCellIndex = ((pos[index] - gridMin) - max_distance) * inverseCellWidth; - int xStart = (int)boidCoord.x; - int yStart = (int)boidCoord.y; - int zStart = (int)boidCoord.z; - //int loopCount = 0; int candidateGridId, boidStart, boidEnd, numberNeighboursRule1 = 0, numberNeighboursRule3 = 0; - //printf("Boid Co-ordinate: x: %d ,y: %d, z:%d \n", boidCoord.x, boidCoord.y, boidCoord.z); - for (int x = xStart - 1; x <= xStart + 1; x++) { + //printf("Boid Co-ordinate: x: %d ,y: %d, z:%d \n", maxCellIndex.x, maxCellIndex.y, maxCellIndex.z); + int loopCount = 0; + for (int x = minCellIndex.x; x <= maxCellIndex.x; x++) { if (x < 0 || x >= gridResolution) continue; - for (int y = yStart - 1; y <= yStart + 1; y++) { + for (int y = minCellIndex.y; y <= maxCellIndex.y; y++) { if (y < 0 || y >= gridResolution) continue; - for (int z = zStart - 1; z <= zStart + 1; z++) { + for (int z = minCellIndex.z; z <= maxCellIndex.z; z++) { if (z < 0 || z >= gridResolution) continue; - + loopCount++; candidateGridId = gridIndex3Dto1D(x, y, z, gridResolution); boidStart = gridCellStartIndices[candidateGridId]; boidEnd = gridCellEndIndices[candidateGridId]; diff --git a/src/main.cpp b/src/main.cpp index ddd0e3b..fafcc7b 100644 --- a/src/main.cpp +++ b/src/main.cpp @@ -18,7 +18,7 @@ #define COHERENT_GRID 1 // LOOK-1.2 - change this to adjust particle count in the simulation -const int N_FOR_VIS = 5000; +const int N_FOR_VIS = 50000; const float DT = 0.2f; /** From bb29c1ca4d60dc0594cc9ca04c4c856b7ba1cb70 Mon Sep 17 00:00:00 2001 From: Somanshu Agarwal <43916672+somanshu25@users.noreply.github.com> Date: Sun, 8 Sep 2019 07:31:33 -0400 Subject: [PATCH 07/28] Update README.md --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index d63a6a1..8ec72a5 100644 --- a/README.md +++ b/README.md @@ -1,8 +1,8 @@ **University of Pennsylvania, CIS 565: GPU Programming and Architecture, Project 1 - Flocking** -* (TODO) YOUR NAME HERE - * (TODO) [LinkedIn](), [personal website](), [twitter](), etc. +* SOMANSHU AGARWAL + * [LinkedIn](www.linkedin.com/in/somanshu25) * Tested on: (TODO) Windows 22, i7-2222 @ 2.22GHz 22GB, GTX 222 222MB (Moore 2222 Lab) ### (TODO: Your README) From d3ed6dd1309c0496ce5663a3ad11594554bc5864 Mon Sep 17 00:00:00 2001 From: Somanshu Agarwal <43916672+somanshu25@users.noreply.github.com> Date: Sun, 8 Sep 2019 11:17:06 -0400 Subject: [PATCH 08/28] Update README.md --- README.md | 27 ++++++++++++++++++++++++--- 1 file changed, 24 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 8ec72a5..c227172 100644 --- a/README.md +++ b/README.md @@ -5,7 +5,28 @@ Project 1 - Flocking** * [LinkedIn](www.linkedin.com/in/somanshu25) * Tested on: (TODO) Windows 22, i7-2222 @ 2.22GHz 22GB, GTX 222 222MB (Moore 2222 Lab) -### (TODO: Your README) +### OBJECTIVE + +The main motive of the project is to visualize Boids flocking and do the performance analysis on three implementation ways of flocking: naive, scattered and coherent search. The search was to find the relevant neigbours of each boid and its position and velocity is updates with respect to its neighbours thorugh the three rules: adhesion, dodging and cohesion. The brief implemetation details of these 3 ways and the performance analysis is given below. + +## 1. Naive Implementation + +In the naive implementation, got a particluar boid, we are searching all the other boids and then selecting the relevant neighbours for the position and velocity update of the boid. This for every boid, we are checking other N-1 boids, which is time consuming and inefficient when N is large. + +For the rest of the 2 implementation, we are creating a grid system in which we are enclosing the whole space in a cube with grid cell width setting by the user according to the requirements. With changing the gird cell width, the grid resoltion and the grid cell count will vary and its impact on the performance is also studies in this project. By using the grid system, we are labelling each boid to a grid cell index. + +## 2. Scattered + +In this implementation, we are limiting our search for the boids which are labelled in the cells of the neighbourhood distance we need to check. Thus, we are checking those grid cells which could be enclosed in the sphere inside the cube with the radius as the neighbouring distance. The number of cells enclosed would differ with the length of the grid cells. Having grid width of twice the maximum neighbourhood distance will take 8 cells while the length equal to maximum neighbouring dustance will take 27 cells. For making sure we are selecting those cells which are enclised in the grid cells, we are sorting the array of boid indexes with respect to the grid indexes labelled and then when we select the particular cell index, we get the range of boids we need to check. + +## 3. Coherent + +In this implememntation, we do further optimization in our code by reshuffling the position and velocity boid data with the sorted nboid particluar array indexes so that the memory access of the boid data is also contgous and there will be more cache hits and less misses, which would save the runtime. Thus, we only need the start and end indexes of the boids which are present in the cell to access the boid data rather than the boid array indexes we require in our scattered implementation. + +# Performance Analysis: + +Here are ther graphs showing the frame rate per second of the three implementations when we change the number of boids in the siimulation: + + + -Include screenshots, analysis, etc. (Remember, this is public, so don't put -anything here that you don't want to share with the world.) 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z@9y}g&{4iozbe+~)PVPLBbsbMo>x}BR@y=7Mz{a!;H{T_JK%qpWR=fn{BCmh{{YI> BQd0l` literal 0 HcmV?d00001 From 274ef18b3a2913f4b50154f60a39b9306abcda49 Mon Sep 17 00:00:00 2001 From: Somanshu Agarwal <43916672+somanshu25@users.noreply.github.com> Date: Sun, 8 Sep 2019 11:26:07 -0400 Subject: [PATCH 11/28] Update README.md --- README.md | 11 +++++++++++ 1 file changed, 11 insertions(+) diff --git a/README.md b/README.md index c227172..38a7e95 100644 --- a/README.md +++ b/README.md @@ -27,6 +27,17 @@ In this implememntation, we do further optimization in our code by reshuffling t Here are ther graphs showing the frame rate per second of the three implementations when we change the number of boids in the siimulation: +1 .The graphs showing the FPS with and without visualization for increasing the number of Boids in simulation for all the 3 implementations are: + +![](images/Chart_Boid_Count_With_Visual.png) + + +![](images/Chart_Boid_Count_Without_Visual.png) + +2. The graphs showing increasing the block size for all the 3 implementations are: + +![](images/Chart_Block_Size.png) + From 2a9a3bf4498e360b2ca45061fe173cee85fd4ea6 Mon Sep 17 00:00:00 2001 From: Somanshu Agarwal <43916672+somanshu25@users.noreply.github.com> Date: Sun, 8 Sep 2019 12:49:19 -0400 Subject: [PATCH 12/28] Update README.md --- README.md | 13 +++++++++++++ 1 file changed, 13 insertions(+) diff --git a/README.md b/README.md index 38a7e95..d492396 100644 --- a/README.md +++ b/README.md @@ -34,10 +34,23 @@ Here are ther graphs showing the frame rate per second of the three implementati ![](images/Chart_Boid_Count_Without_Visual.png) +We can see from both the above graphs that FPS rates are more witout visualization. 2. The graphs showing increasing the block size for all the 3 implementations are: ![](images/Chart_Block_Size.png) +## Answers to the questions: +### For each implementation, how does changing the number of boids affect performance? Why do you think this is? +We can see in the graphs above that as the number of boids increase, the performance will decrease as there would be more number of neighbours and boids to check for earch reference boid and thus will increase the runtime. The impact can be seen same in all the 3 implementations, we can observe that the perofrmance is bettern in coherent for higher number of boids as compared to rest of the 2 implementations. + +### For each implementation, how does changing the block count and block size affect performance? Why do you think this is? +With the graph of increasing the block size for all the 3 implementations, we can see that the performance is almost same if we are using the block sioze equal to the multiples of warp size, i.e., 32. We can infer with the fact that the numebr of threads that are released are same even if the block size are increasing. + +### For the coherent uniform grid: did you experience any performance improvements with the more coherent uniform grid? Was this the outcome you expected? Why or why not? +For coherent uniform grid, we see the improved performance with respect to the scattered one + +### Did changing cell width and checking 27 vs 8 neighboring cells affect performance? Why or why not? Be careful: it is insufficient (and possibly incorrect) to say that 27-cell is slower simply because there are more cells to check! +After plotting the line graph for 8 vs 27 neighbouring cells for scattered implementation, we observe that the 27 neighbouring cells is giving slightly better performance as compared to 8 neighbouring cells. One reason could be the smaller cell width will result in more number of grid cells which will include less number of boids as the cells are smaller. Thus, as compare to larger grid cells, it would check the boids which are more probably wthin the neighbouring distance of the boid as the larger cells would have to search the boids which could be farther but just indide the cells. Hence, the performance is slightly better with smaller grid width. From 9effa27181fc67683553e809cda72de751fff801 Mon Sep 17 00:00:00 2001 From: Somanshu Agarwal <43916672+somanshu25@users.noreply.github.com> Date: Sun, 8 Sep 2019 13:31:31 -0400 Subject: [PATCH 13/28] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index d492396..a9123ba 100644 --- a/README.md +++ b/README.md @@ -2,7 +2,7 @@ Project 1 - Flocking** * SOMANSHU AGARWAL - * [LinkedIn](www.linkedin.com/in/somanshu25) + * [LinkedIn](https://www.linkedin.com/in/somanshu25) * Tested on: (TODO) Windows 22, i7-2222 @ 2.22GHz 22GB, GTX 222 222MB (Moore 2222 Lab) ### OBJECTIVE From 317a6a02c7226c3e5fc27fd9cea17cbd2a4b934c Mon Sep 17 00:00:00 2001 From: Somanshu Agarwal <43916672+somanshu25@users.noreply.github.com> Date: Sun, 8 Sep 2019 13:32:26 -0400 Subject: [PATCH 14/28] Add files via upload --- images/project1.gif | Bin 0 -> 3797228 bytes 1 file changed, 0 insertions(+), 0 deletions(-) create mode 100644 images/project1.gif 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2 insertions(+) diff --git a/README.md b/README.md index a9123ba..8b994f4 100644 --- a/README.md +++ b/README.md @@ -1,3 +1,5 @@ +![](images/project1.gif) + **University of Pennsylvania, CIS 565: GPU Programming and Architecture, Project 1 - Flocking** From e0b1032c0627e629a9c426985f9b19926bd5eae6 Mon Sep 17 00:00:00 2001 From: Somanshu Agarwal <43916672+somanshu25@users.noreply.github.com> Date: Sun, 8 Sep 2019 13:42:26 -0400 Subject: [PATCH 16/28] Update README.md --- README.md | 6 +++++- 1 file changed, 5 insertions(+), 1 deletion(-) diff --git a/README.md b/README.md index 8b994f4..6acf0ac 100644 --- a/README.md +++ b/README.md @@ -5,7 +5,7 @@ Project 1 - Flocking** * SOMANSHU AGARWAL * [LinkedIn](https://www.linkedin.com/in/somanshu25) -* Tested on: (TODO) Windows 22, i7-2222 @ 2.22GHz 22GB, GTX 222 222MB (Moore 2222 Lab) +* Tested on: Windows 10, i7-6700 @ 3.4GHz 16GB, Quadro P 100 12 233MB (Moore 100B Lab) ### OBJECTIVE @@ -41,6 +41,10 @@ We can see from both the above graphs that FPS rates are more witout visualizati ![](images/Chart_Block_Size.png) +3. The graph for observing the grid cell width is 2*(neighbouring distance) vs when grid cell width is neighbouring distance is shown below, where the neighbouring distance is the maximum of all the ruleDistances for the neighbour checks. + +![](images/Chart_Grid_CellWidth_Change.png) + ## Answers to the questions: ### For each implementation, how does changing the number of boids affect performance? Why do you think this is? We can see in the graphs above that as the number of boids increase, the performance will decrease as there would be more number of neighbours and boids to check for earch reference boid and thus will increase the runtime. The impact can be seen same in all the 3 implementations, we can observe that the perofrmance is bettern in coherent for higher number of boids as compared to rest of the 2 implementations. From 5243a7a2c9fd5ef8a7cfb591adbf6bb2bb358f03 Mon Sep 17 00:00:00 2001 From: Somanshu Agarwal <43916672+somanshu25@users.noreply.github.com> Date: Sun, 8 Sep 2019 13:51:52 -0400 Subject: [PATCH 17/28] Update README.md --- README.md | 7 +++++++ 1 file changed, 7 insertions(+) diff --git a/README.md b/README.md index 6acf0ac..4be7169 100644 --- a/README.md +++ b/README.md @@ -15,16 +15,23 @@ The main motive of the project is to visualize Boids flocking and do the perform In the naive implementation, got a particluar boid, we are searching all the other boids and then selecting the relevant neighbours for the position and velocity update of the boid. This for every boid, we are checking other N-1 boids, which is time consuming and inefficient when N is large. +### Grid System For the rest of the 2 implementation, we are creating a grid system in which we are enclosing the whole space in a cube with grid cell width setting by the user according to the requirements. With changing the gird cell width, the grid resoltion and the grid cell count will vary and its impact on the performance is also studies in this project. By using the grid system, we are labelling each boid to a grid cell index. +![](images/Boids Ugrid base.png) + ## 2. Scattered In this implementation, we are limiting our search for the boids which are labelled in the cells of the neighbourhood distance we need to check. Thus, we are checking those grid cells which could be enclosed in the sphere inside the cube with the radius as the neighbouring distance. The number of cells enclosed would differ with the length of the grid cells. Having grid width of twice the maximum neighbourhood distance will take 8 cells while the length equal to maximum neighbouring dustance will take 27 cells. For making sure we are selecting those cells which are enclised in the grid cells, we are sorting the array of boid indexes with respect to the grid indexes labelled and then when we select the particular cell index, we get the range of boids we need to check. +![](images/Boids Ugrids buffers naive.png) + ## 3. Coherent In this implememntation, we do further optimization in our code by reshuffling the position and velocity boid data with the sorted nboid particluar array indexes so that the memory access of the boid data is also contgous and there will be more cache hits and less misses, which would save the runtime. Thus, we only need the start and end indexes of the boids which are present in the cell to access the boid data rather than the boid array indexes we require in our scattered implementation. +![](Boids Ugrids buffers data coherent.png) + # Performance Analysis: Here are ther graphs showing the frame rate per second of the three implementations when we change the number of boids in the siimulation: From 8dd5d11e8ab9e9220a107e1632eb76cabc1ebf87 Mon Sep 17 00:00:00 2001 From: Somanshu Agarwal <43916672+somanshu25@users.noreply.github.com> Date: Sun, 8 Sep 2019 13:52:33 -0400 Subject: [PATCH 18/28] Update README.md --- README.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 4be7169..2f62b7c 100644 --- a/README.md +++ b/README.md @@ -18,19 +18,19 @@ In the naive implementation, got a particluar boid, we are searching all the oth ### Grid System For the rest of the 2 implementation, we are creating a grid system in which we are enclosing the whole space in a cube with grid cell width setting by the user according to the requirements. With changing the gird cell width, the grid resoltion and the grid cell count will vary and its impact on the performance is also studies in this project. By using the grid system, we are labelling each boid to a grid cell index. -![](images/Boids Ugrid base.png) +![](images/Boids_Ugrid_base.png) ## 2. Scattered In this implementation, we are limiting our search for the boids which are labelled in the cells of the neighbourhood distance we need to check. Thus, we are checking those grid cells which could be enclosed in the sphere inside the cube with the radius as the neighbouring distance. The number of cells enclosed would differ with the length of the grid cells. Having grid width of twice the maximum neighbourhood distance will take 8 cells while the length equal to maximum neighbouring dustance will take 27 cells. For making sure we are selecting those cells which are enclised in the grid cells, we are sorting the array of boid indexes with respect to the grid indexes labelled and then when we select the particular cell index, we get the range of boids we need to check. -![](images/Boids Ugrids buffers naive.png) +![](images/Boids_Ugrids_buffers_naive.png) ## 3. Coherent In this implememntation, we do further optimization in our code by reshuffling the position and velocity boid data with the sorted nboid particluar array indexes so that the memory access of the boid data is also contgous and there will be more cache hits and less misses, which would save the runtime. Thus, we only need the start and end indexes of the boids which are present in the cell to access the boid data rather than the boid array indexes we require in our scattered implementation. -![](Boids Ugrids buffers data coherent.png) +![](images/Boids_Ugrids_buffers_data_coherent.png) # Performance Analysis: From 5d6b8bbfe07c6d35874e52c7b8fed9bc17ca1d05 Mon Sep 17 00:00:00 2001 From: Somanshu Agarwal <43916672+somanshu25@users.noreply.github.com> Date: Sun, 8 Sep 2019 13:53:10 -0400 Subject: [PATCH 19/28] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 2f62b7c..bf9a12b 100644 --- a/README.md +++ b/README.md @@ -18,7 +18,7 @@ In the naive implementation, got a particluar boid, we are searching all the oth ### Grid System For the rest of the 2 implementation, we are creating a grid system in which we are enclosing the whole space in a cube with grid cell width setting by the user according to the requirements. With changing the gird cell width, the grid resoltion and the grid cell count will vary and its impact on the performance is also studies in this project. By using the grid system, we are labelling each boid to a grid cell index. -![](images/Boids_Ugrid_base.png) +![](images/Boids Ugrid base.png) ## 2. Scattered From 5752545fb16b6f731d118f2e58936de9072d054e Mon Sep 17 00:00:00 2001 From: Somanshu Agarwal <43916672+somanshu25@users.noreply.github.com> Date: Sun, 8 Sep 2019 13:53:38 -0400 Subject: [PATCH 20/28] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index bf9a12b..e8b9f2b 100644 --- a/README.md +++ b/README.md @@ -18,7 +18,7 @@ In the naive implementation, got a particluar boid, we are searching all the oth ### Grid System For the rest of the 2 implementation, we are creating a grid system in which we are enclosing the whole space in a cube with grid cell width setting by the user according to the requirements. With changing the gird cell width, the grid resoltion and the grid cell count will vary and its impact on the performance is also studies in this project. By using the grid system, we are labelling each boid to a grid cell index. -![](images/Boids Ugrid base.png) +![](images/Boids%Ugrid%base.png) ## 2. Scattered From e1bdc1b7006334b904ed5b456fe187ca5f8863a4 Mon Sep 17 00:00:00 2001 From: Somanshu Agarwal <43916672+somanshu25@users.noreply.github.com> Date: Sun, 8 Sep 2019 13:54:12 -0400 Subject: [PATCH 21/28] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index e8b9f2b..bfc26e4 100644 --- a/README.md +++ b/README.md @@ -18,7 +18,7 @@ In the naive implementation, got a particluar boid, we are searching all the oth ### Grid System For the rest of the 2 implementation, we are creating a grid system in which we are enclosing the whole space in a cube with grid cell width setting by the user according to the requirements. With changing the gird cell width, the grid resoltion and the grid cell count will vary and its impact on the performance is also studies in this project. By using the grid system, we are labelling each boid to a grid cell index. -![](images/Boids%Ugrid%base.png) +![](https://github.com/somanshu25/Project1-CUDA-Flocking/blob/master/images/Boids%20Ugrid%20base.png) ## 2. Scattered From dab32bd88f1f9f88171d4d914c58f619babf5180 Mon Sep 17 00:00:00 2001 From: Somanshu Agarwal <43916672+somanshu25@users.noreply.github.com> Date: Sun, 8 Sep 2019 13:54:54 -0400 Subject: [PATCH 22/28] Update README.md --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index bfc26e4..7afb79b 100644 --- a/README.md +++ b/README.md @@ -24,13 +24,13 @@ For the rest of the 2 implementation, we are creating a grid system in which we In this implementation, we are limiting our search for the boids which are labelled in the cells of the neighbourhood distance we need to check. Thus, we are checking those grid cells which could be enclosed in the sphere inside the cube with the radius as the neighbouring distance. The number of cells enclosed would differ with the length of the grid cells. Having grid width of twice the maximum neighbourhood distance will take 8 cells while the length equal to maximum neighbouring dustance will take 27 cells. For making sure we are selecting those cells which are enclised in the grid cells, we are sorting the array of boid indexes with respect to the grid indexes labelled and then when we select the particular cell index, we get the range of boids we need to check. -![](images/Boids_Ugrids_buffers_naive.png) +![](https://github.com/somanshu25/Project1-CUDA-Flocking/blob/master/images/Boids%20Ugrids%20buffers%20naive.png) ## 3. Coherent In this implememntation, we do further optimization in our code by reshuffling the position and velocity boid data with the sorted nboid particluar array indexes so that the memory access of the boid data is also contgous and there will be more cache hits and less misses, which would save the runtime. Thus, we only need the start and end indexes of the boids which are present in the cell to access the boid data rather than the boid array indexes we require in our scattered implementation. -![](images/Boids_Ugrids_buffers_data_coherent.png) +![](https://github.com/somanshu25/Project1-CUDA-Flocking/blob/master/images/Boids%20Ugrids%20buffers%20data%20coherent.png) # Performance Analysis: From 1944a09dedf82ff950e772ed9299f8d5b5ce6c17 Mon Sep 17 00:00:00 2001 From: Somanshu Agarwal <43916672+somanshu25@users.noreply.github.com> Date: Sun, 8 Sep 2019 13:57:02 -0400 Subject: [PATCH 23/28] Update README.md --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 7afb79b..3d831e5 100644 --- a/README.md +++ b/README.md @@ -15,13 +15,13 @@ The main motive of the project is to visualize Boids flocking and do the perform In the naive implementation, got a particluar boid, we are searching all the other boids and then selecting the relevant neighbours for the position and velocity update of the boid. This for every boid, we are checking other N-1 boids, which is time consuming and inefficient when N is large. +## 2. Scattered + ### Grid System For the rest of the 2 implementation, we are creating a grid system in which we are enclosing the whole space in a cube with grid cell width setting by the user according to the requirements. With changing the gird cell width, the grid resoltion and the grid cell count will vary and its impact on the performance is also studies in this project. By using the grid system, we are labelling each boid to a grid cell index. ![](https://github.com/somanshu25/Project1-CUDA-Flocking/blob/master/images/Boids%20Ugrid%20base.png) -## 2. Scattered - In this implementation, we are limiting our search for the boids which are labelled in the cells of the neighbourhood distance we need to check. Thus, we are checking those grid cells which could be enclosed in the sphere inside the cube with the radius as the neighbouring distance. The number of cells enclosed would differ with the length of the grid cells. Having grid width of twice the maximum neighbourhood distance will take 8 cells while the length equal to maximum neighbouring dustance will take 27 cells. For making sure we are selecting those cells which are enclised in the grid cells, we are sorting the array of boid indexes with respect to the grid indexes labelled and then when we select the particular cell index, we get the range of boids we need to check. ![](https://github.com/somanshu25/Project1-CUDA-Flocking/blob/master/images/Boids%20Ugrids%20buffers%20naive.png) From fa95f07ebe073a6183573365dce4c113795a20d4 Mon Sep 17 00:00:00 2001 From: Somanshu Agarwal <43916672+somanshu25@users.noreply.github.com> Date: Sun, 8 Sep 2019 14:10:39 -0400 Subject: [PATCH 24/28] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 3d831e5..a2ca094 100644 --- a/README.md +++ b/README.md @@ -60,7 +60,7 @@ We can see in the graphs above that as the number of boids increase, the perform With the graph of increasing the block size for all the 3 implementations, we can see that the performance is almost same if we are using the block sioze equal to the multiples of warp size, i.e., 32. We can infer with the fact that the numebr of threads that are released are same even if the block size are increasing. ### For the coherent uniform grid: did you experience any performance improvements with the more coherent uniform grid? Was this the outcome you expected? Why or why not? -For coherent uniform grid, we see the improved performance with respect to the scattered one +For coherent uniform grid, we see the improved performance as wew are removing the extra runtime where we are looking for the velocity and the position of the boid data in the memory which is not in sync with the start and end indexes of the grid cell, making more misses in the cache present in on-chip. After rehuffling the velocity and position vectors according to the boids present in the cell as contigous, we spend less time in memory access which improves our performance. ### Did changing cell width and checking 27 vs 8 neighboring cells affect performance? Why or why not? Be careful: it is insufficient (and possibly incorrect) to say that 27-cell is slower simply because there are more cells to check! After plotting the line graph for 8 vs 27 neighbouring cells for scattered implementation, we observe that the 27 neighbouring cells is giving slightly better performance as compared to 8 neighbouring cells. One reason could be the smaller cell width will result in more number of grid cells which will include less number of boids as the cells are smaller. Thus, as compare to larger grid cells, it would check the boids which are more probably wthin the neighbouring distance of the boid as the larger cells would have to search the boids which could be farther but just indide the cells. Hence, the performance is slightly better with smaller grid width. From 8fae7bce234d1bce5d89109ba82ad43044e7e91f Mon Sep 17 00:00:00 2001 From: Somanshu Agarwal <43916672+somanshu25@users.noreply.github.com> Date: Sun, 8 Sep 2019 14:20:16 -0400 Subject: [PATCH 25/28] Update README.md --- README.md | 18 ++++++++---------- 1 file changed, 8 insertions(+), 10 deletions(-) diff --git a/README.md b/README.md index a2ca094..26e8342 100644 --- a/README.md +++ b/README.md @@ -9,32 +9,32 @@ Project 1 - Flocking** ### OBJECTIVE -The main motive of the project is to visualize Boids flocking and do the performance analysis on three implementation ways of flocking: naive, scattered and coherent search. The search was to find the relevant neigbours of each boid and its position and velocity is updates with respect to its neighbours thorugh the three rules: adhesion, dodging and cohesion. The brief implemetation details of these 3 ways and the performance analysis is given below. +The main motive of the project is to visualize Boids flocking and do the performance analysis on three implementation ways of flocking: naive, scattered and coherent search. The search algorithms find the relevant neigbours for each boid and update its position and velocity with respect to the neighbours through the three rules: adhesion, dodging and cohesion. The brief implemetation details of these 3 ways and the performance analysis is given below. ## 1. Naive Implementation -In the naive implementation, got a particluar boid, we are searching all the other boids and then selecting the relevant neighbours for the position and velocity update of the boid. This for every boid, we are checking other N-1 boids, which is time consuming and inefficient when N is large. +In the naive implementation, for a particluar boid, we are searching all the other boids and then selecting the relevant neighbours for the position and velocity update of that boid. Thus for every boid, we are checking other N-1 boids, which is time consuming and inefficient when N is fairly large. ## 2. Scattered ### Grid System -For the rest of the 2 implementation, we are creating a grid system in which we are enclosing the whole space in a cube with grid cell width setting by the user according to the requirements. With changing the gird cell width, the grid resoltion and the grid cell count will vary and its impact on the performance is also studies in this project. By using the grid system, we are labelling each boid to a grid cell index. +For the rest of the 2 implementations, we are creating a grid system in which we are enclosing the whole space in a cube with grid cell width setting by the user according to the requirements. With changing the gird cell width, the grid resoltion and the grid cell count will vary and its impact on the performance is also studied in this project. By using the grid system, we are labelling each boid to a grid cell index. ![](https://github.com/somanshu25/Project1-CUDA-Flocking/blob/master/images/Boids%20Ugrid%20base.png) -In this implementation, we are limiting our search for the boids which are labelled in the cells of the neighbourhood distance we need to check. Thus, we are checking those grid cells which could be enclosed in the sphere inside the cube with the radius as the neighbouring distance. The number of cells enclosed would differ with the length of the grid cells. Having grid width of twice the maximum neighbourhood distance will take 8 cells while the length equal to maximum neighbouring dustance will take 27 cells. For making sure we are selecting those cells which are enclised in the grid cells, we are sorting the array of boid indexes with respect to the grid indexes labelled and then when we select the particular cell index, we get the range of boids we need to check. +In this implementation, we are limiting our search for the boids which are labelled in the cells of the neighbourhood distance we need to check. Thus, we are checking those grid cells which could be enclosed in the sphere inside the cube with the radius as the neighbouring distance for the boid. The number of cells enclosed would differ with the cell width length of the grid cells. Having grid width of twice the maximum neighbourhood distance will take maximum 8 cells while the length equal to maximum neighbouring distance will take maximum 27 cells. For making sure we are selecting those cells which are enclosed in the grid cells, we are sorting the array of boid indexes with respect to the grid indexes labelled and then when we are storing the start and end boid index for a particular grid cell. Thus, our search for the true neighbours are limited to the range of boid indexes in the start and end indexes rather than the whole N-1. ![](https://github.com/somanshu25/Project1-CUDA-Flocking/blob/master/images/Boids%20Ugrids%20buffers%20naive.png) ## 3. Coherent -In this implememntation, we do further optimization in our code by reshuffling the position and velocity boid data with the sorted nboid particluar array indexes so that the memory access of the boid data is also contgous and there will be more cache hits and less misses, which would save the runtime. Thus, we only need the start and end indexes of the boids which are present in the cell to access the boid data rather than the boid array indexes we require in our scattered implementation. +In this implememntation, we do further optimization in our code by reshuffling the position and velocity boid data with the sorted nboid particluar array indexes so that the memory access of the boid data is also contigous and there will be more cache hits and less misses, which would save the runtime. Thus, we only need the start and end indexes of the boids which are present in the cell to access the boid data rather than the middleman boid array indexes that was required in our previous scattered implementation. ![](https://github.com/somanshu25/Project1-CUDA-Flocking/blob/master/images/Boids%20Ugrids%20buffers%20data%20coherent.png) # Performance Analysis: -Here are ther graphs showing the frame rate per second of the three implementations when we change the number of boids in the siimulation: +Here are the graphs showing the frame rate per second of the three implementations when we change the number of boids in the siimulation: (Note that I'm taking the FPS ratings from the window title where the display is shown) 1 .The graphs showing the FPS with and without visualization for increasing the number of Boids in simulation for all the 3 implementations are: @@ -43,8 +43,8 @@ Here are ther graphs showing the frame rate per second of the three implementati ![](images/Chart_Boid_Count_Without_Visual.png) -We can see from both the above graphs that FPS rates are more witout visualization. -2. The graphs showing increasing the block size for all the 3 implementations are: +We can see from both the above graphs that FPS rates are more witout visualization. We observe that the simulation runs well for 10K boids for naive, 100K for scattered and 200K for coherent, assuming the value of FPS for which simulations runs decent till 20-30 FPS. +2. The graphs showing increasing the block size for all the 3 implementations are (taking number of boids to be 50K): ![](images/Chart_Block_Size.png) @@ -65,5 +65,3 @@ For coherent uniform grid, we see the improved performance as wew are removing t ### Did changing cell width and checking 27 vs 8 neighboring cells affect performance? Why or why not? Be careful: it is insufficient (and possibly incorrect) to say that 27-cell is slower simply because there are more cells to check! After plotting the line graph for 8 vs 27 neighbouring cells for scattered implementation, we observe that the 27 neighbouring cells is giving slightly better performance as compared to 8 neighbouring cells. One reason could be the smaller cell width will result in more number of grid cells which will include less number of boids as the cells are smaller. Thus, as compare to larger grid cells, it would check the boids which are more probably wthin the neighbouring distance of the boid as the larger cells would have to search the boids which could be farther but just indide the cells. 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z@9y}g&{4iozbe+~)PVPLBbsbMo>x}BR@y=7Mz{a!;H{T_JK%qpWR=fn{BCmh{{YI> BQd0l` From b8af366dca35905ae0f761ba060658998e095aa5 Mon Sep 17 00:00:00 2001 From: Somanshu Agarwal <43916672+somanshu25@users.noreply.github.com> Date: Sun, 8 Sep 2019 14:30:49 -0400 Subject: [PATCH 27/28] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 26e8342..5be7a94 100644 --- a/README.md +++ b/README.md @@ -18,7 +18,7 @@ In the naive implementation, for a particluar boid, we are searching all the oth ## 2. Scattered ### Grid System -For the rest of the 2 implementations, we are creating a grid system in which we are enclosing the whole space in a cube with grid cell width setting by the user according to the requirements. With changing the gird cell width, the grid resoltion and the grid cell count will vary and its impact on the performance is also studied in this project. By using the grid system, we are labelling each boid to a grid cell index. +For the rest of the 2 implementations, we are creating a grid system in which we are enclosing the whole space in a cube with grid cell width setting by the user according to the requirements. With changing the gird cell width, the grid resoltion and the grid cell count will vary and its impact on the performance is also studied in this project. By using the grid system, we are labelling each boid to a particular grid cell index. ![](https://github.com/somanshu25/Project1-CUDA-Flocking/blob/master/images/Boids%20Ugrid%20base.png) From e529e79ab4bf67160822f0374d5687964a17719c Mon Sep 17 00:00:00 2001 From: Somanshu Agarwal <43916672+somanshu25@users.noreply.github.com> Date: Sun, 8 Sep 2019 14:35:52 -0400 Subject: [PATCH 28/28] Update README.md --- README.md | 1 + 1 file changed, 1 insertion(+) diff --git a/README.md b/README.md index 5be7a94..598fb88 100644 --- a/README.md +++ b/README.md @@ -48,6 +48,7 @@ We can see from both the above graphs that FPS rates are more witout visualizati ![](images/Chart_Block_Size.png) + 3. The graph for observing the grid cell width is 2*(neighbouring distance) vs when grid cell width is neighbouring distance is shown below, where the neighbouring distance is the maximum of all the ruleDistances for the neighbour checks. ![](images/Chart_Grid_CellWidth_Change.png)

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