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Tractor Rear Axle (V19cg-2) Analysis Type Power Supply Module (V19cg-1) Analysis Type
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The specifications will include two GK210 chips featuring 4992 CUDA. If changes are made when running these benchmarks, for example, to run more variations of cores, if the benchmarks are run on older/slower hardware, or if hardware with less than 128GB of physical memory is used, then longer runtimes can be expectedĪnsys Mechanical Run Time Benchmark: NVIDIA Tesla V100S vs Quadro RTX 6000 vs CPU OnlyĪnsys Benchmarks - Mechanical Core Solver Rating: NVIDIA Tesla V100S vs Quadro RTX 6000 vs CPU Only Since the Tesla K80 is a dual-chip graphics card, it will feature two GK210 chips which are codenamed as the GK210-DUO. The benchmarks have been designed to run in about 48 hours on current generation hardware with at least 128 GB of RAM. Franois Courteille Senior Solutions Architect, NVIDIA . FP64 64-bit (double precision) floating point calculation Tesla K80, 1.87+ TFLOPS Tesla P100, 4.75.3 TFLOPS Quadro GP100, 5.2 TFLOPS Tesla V100, 77.8. *NVIDIA Tesla V100S is passively cooled and recommended only if used in a rack-mounted configuration for this type of workstation. GPU: NVIDIA Quadro V100S*, NVIDIA Quadro RTX 6000 Mem: 512GB RAM. For more on these results, read Bank on It. In short, a single Tesla K80 driven by two CPU cores outperforms all previously audited systems in terms of pure performance and power efficiency. 2x Gold 6252 24C vs 2x 6256 12C + V100S.Įxxact Ansys Certified Rack-mountable Workstation - CPU: 2x Intel Xeon Gold 6256 3.60 GHz 12-Core CPUs, HT Off. Recently, STAC Research published astonishing performance results for the STAC-A2 benchmarks on an NVIDIA Tesla K80. In some cases, a sole high core count processor even outperforms a solution with CPU + GPU acceleration. Besides GPU, high core count CPU is playing an essential role in Ansys application performance.V100S performance is almost 2x better than RTX 6000/8000 in some cases (V19sp-X cases).Tesla V100S has nearly 2x better performance on models (V19sp-X) using sparse solver due to its higher FP64 performance.Cases are selected to represent typical usage and cover a range of mesh sizes and physical models." Key Findings To accomplish this goal, Ansys provides the suite of simulation cases that make up the Ansys benchmark suite to its hardware partners for their use in benchmarking hardware performance then the data is reported to Ansys and compiled for this site. TESLA K80 NVIDIA 24GB GDDR5 CUDA GPU Graphics Card 900-22080-6300 -000. The benchmarks can be used to compare the performance of different hardware platforms when running Ansys solvers. According to Ansys: "Ansys benchmarks provide comprehensive and fair comparative information concerning the performance of Ansys solvers on available hardware platforms. In this blog, we examine Benchmark results for Ansys Mechanical on NVIDIA GPUs.