chibi@2004:~$ ls NVIDIA_CUDA-11.4_Samples デスクトップ cuda-repo-ubuntu2004-11-4-local_11.4.4-470.82.01-1_amd64.deb ドキュメント libcudnn8-dev_8.3.0.98-1+cuda11.5_amd64.deb ビデオ libcudnn8-samples_8.3.0.98-1+cuda11.5_amd64.deb ピクチャ libcudnn8_8.3.0.98-1+cuda11.5_amd64.deb ミュージック ダウンロード 公開 テンプレート chibi@2004:~$ cd NVIDIA_CUDA-11.4_Samples chibi@2004:~/NVIDIA_CUDA-11.4_Samples$ ls 0_Simple 2_Graphics 4_Finance 6_Advanced EULA.txt common 1_Utilities 3_Imaging 5_Simulations 7_CUDALibraries Makefile chibi@2004:~/NVIDIA_CUDA-11.4_Samples$ cd 1_Utilities chibi@2004:~/NVIDIA_CUDA-11.4_Samples/1_Utilities$ ls UnifiedMemoryPerf deviceQuery p2pBandwidthLatencyTest bandwidthTest deviceQueryDrv topologyQuery chibi@2004:~/NVIDIA_CUDA-11.4_Samples/1_Utilities$ cd deviceQuery chibi@2004:~/NVIDIA_CUDA-11.4_Samples/1_Utilities/deviceQuery$ make /usr/local/cuda-11.4/bin/nvcc -ccbin g++ -I../../common/inc -m64 --threads 0 --std=c++11 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_86,code=compute_86 -o deviceQuery.o -c deviceQuery.cpp nvcc warning : The 'compute_35', 'compute_37', 'compute_50', 'sm_35', 'sm_37' and 'sm_50' architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning). /usr/local/cuda-11.4/bin/nvcc -ccbin g++ -m64 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_86,code=compute_86 -o deviceQuery deviceQuery.o nvcc warning : The 'compute_35', 'compute_37', 'compute_50', 'sm_35', 'sm_37' and 'sm_50' architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning). mkdir -p ../../bin/x86_64/linux/release cp deviceQuery ../../bin/x86_64/linux/release chibi@2004:~/NVIDIA_CUDA-11.4_Samples/1_Utilities/deviceQuery$ ./deviceQuery ./deviceQuery Starting... CUDA Device Query (Runtime API) version (CUDART static linking) Detected 1 CUDA Capable device(s) Device 0: "NVIDIA RTX A5000" CUDA Driver Version / Runtime Version 11.4 / 11.4 CUDA Capability Major/Minor version number: 8.6 Total amount of global memory: 24256 MBytes (25434652672 bytes) (064) Multiprocessors, (128) CUDA Cores/MP: 8192 CUDA Cores GPU Max Clock rate: 1695 MHz (1.70 GHz) Memory Clock rate: 8001 Mhz Memory Bus Width: 384-bit L2 Cache Size: 6291456 bytes Maximum Texture Dimension Size (x,y,z) 1D=(131072), 2D=(131072, 65536), 3D=(16384, 16384, 16384) Maximum Layered 1D Texture Size, (num) layers 1D=(32768), 2048 layers Maximum Layered 2D Texture Size, (num) layers 2D=(32768, 32768), 2048 layers Total amount of constant memory: 65536 bytes Total amount of shared memory per block: 49152 bytes Total shared memory per multiprocessor: 102400 bytes Total number of registers available per block: 65536 Warp size: 32 Maximum number of threads per multiprocessor: 1536 Maximum number of threads per block: 1024 Max dimension size of a thread block (x,y,z): (1024, 1024, 64) Max dimension size of a grid size (x,y,z): (2147483647, 65535, 65535) Maximum memory pitch: 2147483647 bytes Texture alignment: 512 bytes Concurrent copy and kernel execution: Yes with 2 copy engine(s) Run time limit on kernels: Yes Integrated GPU sharing Host Memory: No Support host page-locked memory mapping: Yes Alignment requirement for Surfaces: Yes Device has ECC support: Disabled Device supports Unified Addressing (UVA): Yes Device supports Managed Memory: Yes Device supports Compute Preemption: Yes Supports Cooperative Kernel Launch: Yes Supports MultiDevice Co-op Kernel Launch: Yes Device PCI Domain ID / Bus ID / location ID: 0 / 65 / 0 Compute Mode: < Default (multiple host threads can use ::cudaSetDevice() with device simultaneously) > deviceQuery, CUDA Driver = CUDART, CUDA Driver Version = 11.4, CUDA Runtime Version = 11.4, NumDevs = 1 Result = PASS chibi@2004:~/NVIDIA_CUDA-11.4_Samples/1_Utilities/deviceQuery$ cd ~/NVIDIA_CUDA-11.4_Samples/ chibi@2004:~/NVIDIA_CUDA-11.4_Samples$ ls 0_Simple 2_Graphics 4_Finance 6_Advanced EULA.txt bin 1_Utilities 3_Imaging 5_Simulations 7_CUDALibraries Makefile common chibi@2004:~/NVIDIA_CUDA-11.4_Samples$ cd 5_Simulations chibi@2004:~/NVIDIA_CUDA-11.4_Samples/5_Simulations$ ls fluidsGL nbody nbody_screen particles fluidsGLES nbody_opengles oceanFFT smokeParticles chibi@2004:~/NVIDIA_CUDA-11.4_Samples/5_Simulations$ cd nbody chibi@2004:~/NVIDIA_CUDA-11.4_Samples/5_Simulations/nbody$ make >>> GCC Version is greater or equal to 5.1.0 <<< /usr/local/cuda-11.4/bin/nvcc -ccbin g++ -I../../common/inc -m64 -ftz=true --threads 0 --std=c++11 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_86,code=compute_86 -o bodysystemcuda.o -c bodysystemcuda.cu nvcc warning : The 'compute_35', 'compute_37', 'compute_50', 'sm_35', 'sm_37' and 'sm_50' architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning). /usr/local/cuda-11.4/bin/nvcc -ccbin g++ -I../../common/inc -m64 -ftz=true --threads 0 --std=c++11 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_86,code=compute_86 -o nbody.o -c nbody.cpp nvcc warning : The 'compute_35', 'compute_37', 'compute_50', 'sm_35', 'sm_37' and 'sm_50' architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning). /usr/local/cuda-11.4/bin/nvcc -ccbin g++ -I../../common/inc -m64 -ftz=true --threads 0 --std=c++11 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_86,code=compute_86 -o render_particles.o -c render_particles.cpp nvcc warning : The 'compute_35', 'compute_37', 'compute_50', 'sm_35', 'sm_37' and 'sm_50' architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning). /usr/local/cuda-11.4/bin/nvcc -ccbin g++ -m64 -gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37 -gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 -gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -gencode arch=compute_86,code=compute_86 -o nbody bodysystemcuda.o nbody.o render_particles.o -L/usr/lib/nvidia-compute-utils-470 -lGL -lGLU -lglut nvcc warning : The 'compute_35', 'compute_37', 'compute_50', 'sm_35', 'sm_37' and 'sm_50' architectures are deprecated, and may be removed in a future release (Use -Wno-deprecated-gpu-targets to suppress warning). mkdir -p ../../bin/x86_64/linux/release cp nbody ../../bin/x86_64/linux/release chibi@2004:~/NVIDIA_CUDA-11.4_Samples/5_Simulations/nbody$ ./nbody -benchmark -numbodies=256000 -device=0 Run "nbody -benchmark [-numbodies=]" to measure performance. -fullscreen (run n-body simulation in fullscreen mode) -fp64 (use double precision floating point values for simulation) -hostmem (stores simulation data in host memory) -benchmark (run benchmark to measure performance) -numbodies= (number of bodies (>= 1) to run in simulation) -device= (where d=0,1,2.... for the CUDA device to use) -numdevices= (where i=(number of CUDA devices > 0) to use for simulation) -compare (compares simulation results running once on the default GPU and once on the CPU) -cpu (run n-body simulation on the CPU) -tipsy= (load a tipsy model file for simulation) NOTE: The CUDA Samples are not meant for performance measurements. Results may vary when GPU Boost is enabled. > Windowed mode > Simulation data stored in video memory > Single precision floating point simulation > 1 Devices used for simulation gpuDeviceInit() CUDA Device [0]: "Ampere > Compute 8.6 CUDA device: [NVIDIA RTX A5000] number of bodies = 256000 256000 bodies, total time for 10 iterations: 933.842 ms = 701.789 billion interactions per second = 14035.780 single-precision GFLOP/s at 20 flops per interaction chibi@2004:~/NVIDIA_CUDA-11.4_Samples/5_Simulations/nbody$ ./nbody -fp64 -benchmark -numbodies=256000 -device=0 Run "nbody -benchmark [-numbodies=]" to measure performance. -fullscreen (run n-body simulation in fullscreen mode) -fp64 (use double precision floating point values for simulation) -hostmem (stores simulation data in host memory) -benchmark (run benchmark to measure performance) -numbodies= (number of bodies (>= 1) to run in simulation) -device= (where d=0,1,2.... for the CUDA device to use) -numdevices= (where i=(number of CUDA devices > 0) to use for simulation) -compare (compares simulation results running once on the default GPU and once on the CPU) -cpu (run n-body simulation on the CPU) -tipsy= (load a tipsy model file for simulation) NOTE: The CUDA Samples are not meant for performance measurements. Results may vary when GPU Boost is enabled. > Windowed mode > Simulation data stored in video memory > Double precision floating point simulation > 1 Devices used for simulation gpuDeviceInit() CUDA Device [0]: "Ampere > Compute 8.6 CUDA device: [NVIDIA RTX A5000] number of bodies = 256000 256000 bodies, total time for 10 iterations: 56184.371 ms = 11.664 billion interactions per second = 349.934 double-precision GFLOP/s at 30 flops per interaction chibi@2004:~/NVIDIA_CUDA-11.4_Samples/5_Simulations/nbody$ ./nbody -fp32 -benchm ark -numbodies=256000 -device=0 Run "nbody -benchmark [-numbodies=]" to measure performance. -fullscreen (run n-body simulation in fullscreen mode) -fp64 (use double precision floating point values for simulation) -hostmem (stores simulation data in host memory) -benchmark (run benchmark to measure performance) -numbodies= (number of bodies (>= 1) to run in simulation) -device= (where d=0,1,2.... for the CUDA device to use) -numdevices= (where i=(number of CUDA devices > 0) to use for simulation) -compare (compares simulation results running once on the default GPU and once on the CPU) -cpu (run n-body simulation on the CPU) -tipsy= (load a tipsy model file for simulation) NOTE: The CUDA Samples are not meant for performance measurements. Results may vary when GPU Boost is enabled. > Windowed mode > Simulation data stored in video memory > Single precision floating point simulation > 1 Devices used for simulation gpuDeviceInit() CUDA Device [0]: "Ampere > Compute 8.6 CUDA device: [NVIDIA RTX A5000] number of bodies = 256000 256000 bodies, total time for 10 iterations: 937.949 ms = 698.716 billion interactions per second = 13974.318 single-precision GFLOP/s at 20 flops per interaction chibi@2004:~/NVIDIA_CUDA-11.4_Samples/5_Simulations/nbody$ ./nbody -benchmark -numbodies=256000 -device=0 Run "nbody -benchmark [-numbodies=]" to measure performance. -fullscreen (run n-body simulation in fullscreen mode) -fp64 (use double precision floating point values for simulation) -hostmem (stores simulation data in host memory) -benchmark (run benchmark to measure performance) -numbodies= (number of bodies (>= 1) to run in simulation) -device= (where d=0,1,2.... for the CUDA device to use) -numdevices= (where i=(number of CUDA devices > 0) to use for simulation) -compare (compares simulation results running once on the default GPU and once on the CPU) -cpu (run n-body simulation on the CPU) -tipsy= (load a tipsy model file for simulation) NOTE: The CUDA Samples are not meant for performance measurements. Results may vary when GPU Boost is enabled. > Windowed mode > Simulation data stored in video memory > Single precision floating point simulation > 1 Devices used for simulation gpuDeviceInit() CUDA Device [0]: "Ampere > Compute 8.6 CUDA device: [NVIDIA RTX A5000] number of bodies = 256000 256000 bodies, total time for 10 iterations: 932.152 ms = 703.061 billion interactions per second = 14061.221 single-precision GFLOP/s at 20 flops per interaction chibi@2004:~/NVIDIA_CUDA-11.4_Samples/5_Simulations/nbody$ ./nbody -f16 -benchma rk -numbodies=256000 -device=0 Run "nbody -benchmark [-numbodies=]" to measure performance. -fullscreen (run n-body simulation in fullscreen mode) -fp64 (use double precision floating point values for simulation) -hostmem (stores simulation data in host memory) -benchmark (run benchmark to measure performance) -numbodies= (number of bodies (>= 1) to run in simulation) -device= (where d=0,1,2.... for the CUDA device to use) -numdevices= (where i=(number of CUDA devices > 0) to use for simulation) -compare (compares simulation results running once on the default GPU and once on the CPU) -cpu (run n-body simulation on the CPU) -tipsy= (load a tipsy model file for simulation) NOTE: The CUDA Samples are not meant for performance measurements. Results may vary when GPU Boost is enabled. > Windowed mode > Simulation data stored in video memory > Single precision floating point simulation > 1 Devices used for simulation gpuDeviceInit() CUDA Device [0]: "Ampere > Compute 8.6 CUDA device: [NVIDIA RTX A5000] number of bodies = 256000 256000 bodies, total time for 10 iterations: 934.663 ms = 701.172 billion interactions per second = 14023.448 single-precision GFLOP/s at 20 flops per interaction chibi@2004:~/NVIDIA_CUDA-11.4_Samples/5_Simulations/nbody$ nvidia-smi nvlink -c GPU 0: NVIDIA RTX A5000 (UUID: GPU-66efacbf-8900-eb52-9ca8-f5c5a351bdcc) chibi@2004:~/NVIDIA_CUDA-11.4_Samples/5_Simulations/nbody$