Vpu technology &gpgpu computing

VPU TECHNOLOGY &GPGPU COMPUTING Arka Ghosh(9007900477a@gmail.com) B.Tech Computer Science & Engineering DELIVERED AT Seacom Engineering College,CSE Dept DATE 7 th April’2011

What Is VPU? VPU is Visual Processing Unit it is more generally known as Graphics Processing Unit or GPU. The Graphics Processing Unit is a MASSIVELY PARALAL & MASSIVELY MULTITHREADED microprocessor. ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],© Arka Ghosh 2011

What is PPU? PPU is physics processing unit. which specialized for calculation of rigid body dynamics, soft body dynamics, collision detection, fluid dynamics, hair and clothing simulation, finite element analysis, and fracturing of objects. ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],© Arka Ghosh 2011

-:INTO THE ARCHITECTURE:- ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],© Arka Ghosh 2011

 Graphics Pipeline  ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],© Arka Ghosh 2011

GPU CLUSTER  ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],© Arka Ghosh 2011

What Is GPGPU? GPGPU stands for general purpose graphics processin unit computing.Using GPU as CPU is the GPGPU computing ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],NVIDIA FLEXES TESLA MUSCLE

CUDA Kernels and Threads ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Data Movement Example int main(void) { float *a_h, *b_h; // host data float *a_d, *b_d; // device data int N = 14, nBytes, i ; nBytes = N*sizeof(float); a_h = (float *)malloc(nBytes); b_h = (float *)malloc(nBytes); cudaMalloc((void **) &a_d, nBytes); cudaMalloc((void **) &b_d, nBytes); for (i=0, i<N; i++) a_h[i] = 100.f + i; cudaMemcpy(a_d, a_h, nBytes, cudaMemcpyHostToDevice); cudaMemcpy(b_d, a_d, nBytes, cudaMemcpyDeviceToDevice); cudaMemcpy(b_h, b_d, nBytes, cudaMemcpyDeviceToHost); for (i=0; i< N; i++) assert( a_h[i] == b_h[i] ); free(a_h); free(b_h); cudaFree(a_d); cudaFree(b_d); return 0; } © Arka Ghosh 2011

© Arka Ghosh2011 10-Series Architecture 240 thread processors execute kernel threads 30 multiprocessors , each contains 8 thread processors One double-precision unit Shared memory enables thread cooperation Thread Processors Multiprocessor Shared Memory Double

Execution Model Software Hardware Threads are executed by thread processors Thread Thread Processor Multiprocessor Thread blocks are executed on multiprocessors Thread blocks do not migrate Several concurrent thread blocks can reside on Thread Block ... Grid Device one multiprocessor - limited by multiprocessor resources (shared memory and register file) A kernel is launched as a grid of thread blocks Only one kernel can execute on a device at one time © Arka Ghosh2011

Time GigaThread Hardware Thread Scheduler Concurrent Kernel Execution + Faster Context Switch Serial Kernel Execution Parallel Kernel Execution Kernel 1 Kernel 1 Kernel 2 Kernel 2 Ker 4 nel Kernel 3 Kernel 5 Kernel 3 Kernel 4 Kernel 5 Kernel 2 Kernel 2 © Arka Ghosh2011

EXAMPLE:-> ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],clear ALL t1=cputime; x=rand(50); y=rand(50); z=rand(50); a=10; b=20; c=30; d=40; f=a*(x^2)+b*(x*y)+c*(y^3)+d*(z^4); net=feedforwardnet(800); net=trainlm(net,x,f); t2=cputime; t3=t2-t1; MATLAB code For Simple ANN For CPU t3=250.2154 For GPU t3=122.25 So we can see that The GPU is nearabout 204% efficient than CPU. © Arka Ghosh 2011

CONCLUSION  ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],© Arka Ghosh 2011

Acknowledgement  ,[object Object],[object Object],[object Object],[object Object],[object Object]

Vpu technology &gpgpu computing

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