Results may vary when GPU Boost is nvidia-smi -L NOTE: The CUDA Samples are not meant for performance measurements. Which limits the number of GPUs that the application can /usr/local/cuda-11.2/samples/bin/x86_64/linux/release$ CUDA_VISIBLE_DEVICES=0,1,2,3.
Run the example one more time by using the CUDA_VISIBLE_DEVICES variable, This indicates that GPUĤ should not be used for high-performance workloads. The application also shows that there is no peer-to-peerĬonnectivity between any GPU and GPU 4. The example above shows the peer-to-peer bandwidth and latency test across all five GPUs, Results may vary when GPU Boost is enabled. P2P=Enabled Latency (P2P Writes) Matrix (us) Unidirectional P2P=Enabled Bandwidth (P2P Writes) Matrix (GB/s)īidirectional P2P=Disabled Bandwidth Matrix (GB/s)īidirectional P2P=Enabled Bandwidth Matrix (GB/s) Unidirectional P2P=Disabled Bandwidth Matrix (GB/s) So you can see lesser Bandwidth (GB/s) and unstable Latency (us) in those cases. ***NOTE: In case a device doesn't have P2P access to other one, it falls back to normal memcopy procedure. p2pBandwidthLatencyTestĭevice: 0, Graphics Device, pciBusID: 1, pciDeviceID: 0, pciDomainID:0ĭevice: 1, Graphics Device, pciBusID: 47, pciDeviceID: 0, pciDomainID:0ĭevice: 2, Graphics Device, pciBusID: 81, pciDeviceID: 0, pciDomainID:0ĭevice: 3, Graphics Device, pciBusID: c2, pciDeviceID: 0, pciDomainID:0ĭevice: 4, DGX Display, pciBusID: c1, pciDeviceID: 0, pciDomainID:0 gencode arch=compute_86,code=compute_86 -o p2pBandwidthLatencyTest p2pBandwidthLatencyTest.oĬp p2pBandwidthLatencyTest $ cd $. gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37 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). gencode arch=compute_86,code=compute_86 -o p2pBandwidthLatencyTest.o -c p2pBandwidthLatencyTest.cu gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 gencode arch=compute_60,code=sm_60 -gencode arch=compute_61,code=sm_61 gencode arch=compute_50,code=sm_50 -gencode arch=compute_52,code=sm_52 usr/local/cuda/bin/nvcc -ccbin g++ -I././common/inc -m64 -threadsĠ -gencode arch=compute_35,code=sm_35 -gencode arch=compute_37,code=sm_37 Output, GPU 0 is the fastest in a DGX Station A100, and GPU ISO/IEC 17025:2005 is not intended to be used as the basis for certification of laboratories.Ĭompliance with regulatory and safety requirements on the operation of laboratories is not covered by ISO/IEC 17025:2005.In the following example, a CUDA application that comes with CUDA samples is run.
Laboratory customers, regulatory authorities and accreditation bodies may also use it in confirming or recognizing the competence of laboratories. ISO/IEC 17025:2005 is for use by laboratories in developing their management system for quality, administrative and technical operations. When a laboratory does not undertake one or more of the activities covered by ISO/IEC 17025:2005, such as sampling and the design/development of new methods, the requirements of those clauses do not apply. ISO/IEC 17025:2005 is applicable to all laboratories regardless of the number of personnel or the extent of the scope of testing and/or calibration activities. These include, for example, first-, second- and third-party laboratories, and laboratories where testing and/or calibration forms part of inspection and product certification. It is applicable to all organizations performing tests and/or calibrations.
It covers testing and calibration performed using standard methods, non-standard methods, and laboratory-developed methods. ISO/IEC 17025:2005 specifies the general requirements for the competence to carry out tests and/or calibrations, including sampling.
0 kommentar(er)
