Getting Started with CUDA

More documents

Recommendations

Info

Supported Features Single Precision Double Precision* Real Complex Real Complex Level 1 ✔ ✔ ✔ Level 2 Level 3 ✔ ✔ cgemm dgemv, dger, dsyr, dtrsv ✔ © 2008 NVIDIA Corporation. zgemm *Double-precision functions only supported on GPUs <strong>with</strong> double-precision hardware
Using CUBLAS Interface to CUBLAS library is in cublas.h Function naming convention cublas + BLAS name eg. cublasSgemm Following BLAS convention, CUBLAS uses column-major storage Error handling CUBLAS core functions do not return an error CUBLAS provides function to retrieve last error recorded CUBLAS helper functions do return an error Implemented using C-based <strong>CUDA</strong> tool chain Interfacing to C/C++ applications is trivial © 2008 NVIDIA Corporation.
Page 1 and 2:
Getting Started with CUDA Greg Ruet
Page 3 and 4: Outline CUDA programming model Basi
Page 5 and 6: CUDA Kernels and Threads Parallel p
Page 7 and 8: Thread Cooperation The Missing Piec
Page 9 and 10: Transparent Scalability Hardware is
Page 11 and 12: 10-Series Architecture 240 thread p
Page 13 and 14: Physical Memory Layout Host “Loca
Page 15 and 16: Key Parallel Abstractions in CUDA T
Page 17 and 18: CUDA Installation CUDA installation
Page 19 and 20: Compiling CUDA Code C/C++ CUDA Appl
Page 23 and 24: GPU Memory Allocation / Release cud
Page 25 and 26: Data Movement Example int main(void
Page 35 and 36: Executing Code on the GPU Kernels a
Page 37 and 38: Launching Kernels Modified C functi
Page 39 and 40: CUDA Built-in Device Variables All
Page 41 and 42: Minimal Kernels __global__ void min
Page 43 and 44: Host Synchronization All kernel lau
Page 45 and 46: Variable Qualifiers (GPU code) __de
Page 47 and 48: GPU Thread Synchronization void __s
Page 49 and 50: Built-in Vector Types Can be used i
Page 51 and 52: CUDA Programming Resources We only
Page 53: CUBLAS Implementation of BLAS (Basi
Page 57 and 58: sgemmExample.c #include #include
Page 61 and 62: More on CUFFT For 2D and 3D transfo
Page 63 and 64: CUFFT Example #include #include #
Page 65: Getting Started with CUDA Greg Ruet
show all

Getting Started with CUDA

Create successful ePaper yourself

Delete template?

Save as template?