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GPU Radionica

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GPU Radionica GPU radionica Luko Gjenero SRCE 30. Siječnja 2013. GPU? 30. Siječnja 2013. Povijest video igara • Najstariji zapisi • 25 Siječanj 1947 • Thomas T. Goldsmith, Jr. • Estle Ray Mann • "cathode ray tube amusement device" 30. Siječnja 2013. Povijest video igara • Prvi pokušaji zabave 30. Siječnja 2013. Povijest video igara • Prva UNIX aplikacija 30. Siječnja 2013. Povijest video igara • Igraći uređaji – 1970te 30. Siječnja 2013. Povijest video igara • Space Invaders 30. Siječnja 2013. Povijest video igara • Prvi 3D pokušaji 30. Siječnja 2013. Povijest video igara • 1990te – flat 30. Siječnja 2013. Povijest video igara • 1990te – texture mapping 30. Siječnja 2013. Povijest video igara • 1990te – 3D akeceleratori 30. Siječnja 2013. Povijest video igara 30. Siječnja 2013. Danas 30. Siječnja 2013. Povijest GPU -> 30. Siječnja 2013. 3D grafika • Renderiranje – Proces kreiranja slike iz modela • Vertex – Vrh poligona (najčešće trokuta) u modelu • Pixel – Najmanji element ekrana koji se može adresirati 30. Siječnja 2013. 3D grafika • Kako od modela do slike -1.069812 1.643532 -0.283202 -1.523047 1.586146 -0.444300 -1.728016 1.344536 -0.656323 -1.815546 1.037839 -0.906679 -1.810727 0.682244 -1.158979 -1.788165 0.455138 -1.301172 -1.764957 0.177459 -1.467339 -1.701842 -0.448811 -1.830056 -> -1.672400 -1.013893 -2.108265 -1.626917 -1.431036 -2.280596 -1.703426 -1.507439 -1.654671 -1.813526 -1.568119 -0.884709 -1.934581 -1.572616 -0.164067 -2.085154 -1.548759 0.671415 -2.223489 -1.516222 1.435532 … 30. Siječnja 2013. Povijest GPU • Prije GPU -> CPU – Slijedno računanje • Količina operacija – Scena sa 100 000 trokuta – Svaki trokut rasterizira se na prosječno 100 pixela – 10 izvora svjetlosti – 4 ciklusa po izvoru – => 400 000 000 ciklusa 30. Siječnja 2013. Povijest GPU • Razvoj počeo u 1980-tima • 1983 Intel napravio iSBX 275 • 1985 Commodore Amiga prvo osobno računalo koje je standardno imalo ugrađen GPU • 1987 IBM napravio 8514 kao prvu grafičku karticu sa “fixed-function” 2D primitivima 30. Siječnja 2013. Fixed function Pipeline • Prihvaća grafičke naredbe i podatke od CPU 30. Siječnja 2013. Fixed function Pipeline • Prihvaća podatke o trokutima • Pretvara podatke u oblik koji HW razumije • Sprema pripremljene podatke u cache 30. Siječnja 2013. Fixed function Pipeline • Vertex shading transform and lighting • Postavlja vrijednosti za pojedini vertex 30. Siječnja 2013. Fixed function Pipeline • Računa bridove trokuta te postavlja jednadžbe za interpolaciju vertx vrijednosti na pixele koje obuhvaća trokut 30. Siječnja 2013. Fixed function Pipeline • Određuje koji pixel pripada kojem trokutu • Interpolira vrijednosti za svaki pojedini pixel 30. Siječnja 2013. Fixed function Pipeline • Određuje konačnu boju za svaki pixel u trokutu 30. Siječnja 2013. Fixed function Pipeline • Raster operation • Izvršava raster operacije koje računaju miješanje boje trokuta koji se preklapaju ovisno o prozirnosti i metodi anitaliasinga 30. Siječnja 2013. Fixed function Pipeline • Frame buffer interface • Vrši upravljanje pisanjem i čitanjem iz memorije 30. Siječnja 2013. 3D akceleratori • 1996 – 3dfx Interactive – Voodoo chipset • Matrox Mystique • S3 ViRGE • ATI Rage • 3D API – OpenGL – DirecX 30. Siječnja 2013. Programirljivi GPU • 2001 – NVIDIA – Omogućila programerima pristup setu instrukcija u fazi transformacija vertexa i modela osvjetljenja (VS/T & L) – Kasnije prošireno na fazu određivanja konačne boje svakog pixela u trokutu (Shader) 30. Siječnja 2013. Programirljivi GPU 30. Siječnja 2013. Programirljivi GPU • Moguće rješavati probleme korištenjem GPU – Podaci zadani preko tekstura i vertex buffera • Problem adresiranja – Izlaz je 2D slika – Limitirani set instrukcija • Nema operacija sa cijelim brojevima • Nema logičkih operacija 30. Siječnja 2013. Programirljivi GPU • 2006 NVIDIA GeForce 8800 – Mapira različite faze grafičkog procesiranja na unificirano polje procesora – CUDA 30. Siječnja 2013. CUDA GPU 30. Siječnja 2013. CUDA 30. Siječnja 2013. CUDA 30. Siječnja 2013. CUDA 30. Siječnja 2013. CUDA 30. Siječnja 2013. CUDA 30. Siječnja 2013. HW - Fermi • Do 16 SM na GPU • Svaki SM može imati 32 jezgre – Izvršava posao u SIMT načinu – Single Instruction Multiple Thread • 16 SM x 32 jezgre = 512 jezgri 30. Siječnja 2013. HW - Fermi • Warp – 32 dretve – Instrukcije se zadaju po warpu • Ukoliko neki operand u warpu nije spreman za izvršavanje – Mijenja se kontekst warpa - > izvršava se drugi warp – Smanjuje se “idle” vrijeme HW – Mijenjanje konteksta mora biti iznimno brzo 30. Siječnja 2013. HW - Fermi • Mijenjanje konteksta – Svi resursi unutar bloka su aktivni za vrijeme izvođenja cijelog bloka • Registri • Dijeljena memorija – Brzo mijenjane konteksta (warpa) je moguće baš zato jer se registri i dijeljena memorija ne moraju stalno spremati i vraćati u aktivno stanje prilikom svake izmjene konteksta • Cilj – dovoljno transakcija da se memorijska sabirnica zasiti • Fermi omogućuje do 48 warpa na SM – Znači max. 1536 dretvi po SM 30. Siječnja 2013. HW - Fermi • Zauzetost SM-a (Occupancy) – Broj warpova / Max. broj warpova • Resursi za blok su ograničeni – Previše resursa po dretvi smanjuje broj warpova u bloku – Broj registara – Količina dijeljene memorije – Veličina bloka 30. Siječnja 2013. HW - Fermi • Registri – Prevođenje s zastavicom --ptxas-options=-v – 32K registara po SM • Primjer 1 – Dretva zauzima 20 registra (+1 implicitni) – Moguće 32K / 21 -> 1560 dretvi • > 1536 -> zauzetost od 100% ili1.0 • Primjer 2 – Dretva zauzima 63 registra po dretvi (+1 implicitni) – Moguće 32K / 64 -> 512 dretvi • < 1536 -> zauzetost od 33.3% ili 0.333 • Max broj registara: --maxrregcount 30. Siječnja 2013. HW - Fermi • Dijeljena memorija – Prevođenje s zastavicom --ptxas-options=-v – 16K ili 48K po SM • Primjer 1 – 48K dijeljene memorije, 32 byte po dretvi – 48K / 32 -> 1536 dretvi – Zauzetost = 100% • Primjer 2 – 16K dijeljene memorije, 32 byte po dretvi – 16K / 32 -> 512 dretvi – Zauzetost = 33.3% 30. Siječnja 2013. HW – Fermi • Veličina bloka – SM može imati do 8 aktivnih blokova Veličina bloka Broj dretvi po SM Zauzetost 32 256 16.7 % 64 512 33.3 % 128 1024 66.6 % 192 1536 100 % 256 2048 100 % 30. Siječnja 2013. HW – Fermi • Preporuke – 66 % zauzetosti – 128-256 veličina bloka (višekratnik 32 - warp) – CUDA_Occupancy_calculator.xls • Dolazi sa Toolkitom • Excel sa formulama za izračunavanje zauzetosti 30. Siječnja 2013. CUDA • Programska sučelja – C/C++ – FORTRAN – OpenACC – OpenCL • Biblioteke – cuFFT – cuBLAS – cuSPARSE 30. Siječnja 2013. CUDA • Instalacija – https://developer.nvidia.com/cuda-downloads • Podržani HW – https://developer.nvidia.com/cuda-gpus 30. Siječnja 2013. CUDA • /usr/lib64/nvidia • /usr/lib64/cuda/ – bin – lib64 – Include • /usr/share/cuda 30. Siječnja 2013. CUDA • Ispis uređaja na PCI priključcima lspci | grep -i nvidia • Ispis podataka o CUDA uređajima nvidia-smi -q 30. Siječnja 2013. CUDA • Environment varijable – CUDA_VISIBLE_DEVICES • Definicija uređaja koje API može koristiti • export CUDA_VISIBLE_DEVICES=0 – CUDA_LAUNCH_BLOCKING • Omogućuje blokirajući poziv kernel funkcije • export CUDA_LAUNCH_BLOCKING=1 30. Siječnja 2013. CRO-NGI • 36 x nVidia Tesla M2075 – Single 1030 Gflops – Double 515 Gflops – 150 GB/s – 6 GB – 448 CUDA jezgre 30. Siječnja 2013. Isabella • 1 x Tesla S2050 – 4 GPU – Single 4.13 Tflops – Double 2 Tflops – 148 GB/s – 12 GB – 448 CUDA jezgri po GPU 30. Siječnja 2013. CUDA • CUDA C API – Definicija funkcija (kernela) koje se izvršavaju na GPU – Rezervacija i oslobađanje memorije na GPU – Komunikacija RAM <-> GPU – Sinkronizacija kernela 30. Siječnja 2013. CUDA kernel // Kernel definition __global__ void KernelName( float* A, float* B, float* C) { int i = threadIdx.x; C[i] = A[i] + B[i]; } 30. Siječnja 2013. CUDA kernel • threadIdx – Id dretve unutar bloka – 1D, 2D ili 3D vektor • blockDim – dimenzije bloka dretvi – 1D, 2D ili 3D vektor • blockIdx – Id bloka unutar grida – 1D, 2D ili 3D vektor 30. Siječnja 2013. CUDA funkcije ● Postoje 3 vrste funkcija – __global__ – __device__ – __host__ 30. Siječnja 2013. CUDA varijable ● Područje dosutpnosti – __device__ – __shared__ – __constant__ – __restrict__ 30. Siječnja 2013. CUDA tipovi podataka • integer i floating point tipovi, signed i unsigned verzije • struct tipovi podataka • vektorski tipovi podataka • float2, float3, float4, int2, int3, … • C++ tipovi podataka nisu ugrađeni – Bolje izbjegavati – string -> char* 30. Siječnja 2013. CUDA built-in funkcije ● Osnovne matematiče operacije – + - / * pow sqrt ... ● Logaritamske – log, log2, log10, log1p, exp, exp2, exp10, expm1 ● Trigonometrijske – sin, cos, tan, asin, acos, atan, sinh, cosh, ... ● Funkcije vezane za teksture i površine ● Atomic funkcije 30. Siječnja 2013. CUDA API ● Include path – /usr/lib64/cuda/include ● Library path – /usr/lib64/cuda/lib64 – /usr/lib64/nvidia/ ● Headers – #include <cuda.h> – #include <cuda_runtime.h> ● 30. Siječnja 2013. CUDA API ● Device – cudaGetDeviceCount – cudaSetDevice – cudaGetDeviceProperties – cudaChooseDevice 30. Siječnja 2013. CUDA API ● Memory – cudaMalloc – cudaMallocHost – cudaMemcpy – cudaFree – cudaFreeHost 30. Siječnja 2013. CUDA API ● Kernel KernelName<<< blocksPerGrid, threadsPerBlock, SharedMemorySize, StreamReference >>> (params, ...); 30. Siječnja 2013. www.srce.hr [email protected] 30. Siječnja 2013. .
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