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cluster:182 [2019/08/07 18:19]
hmeij07 [P100 vs RTX & T4] |
cluster:182 [2019/08/12 14:08]
hmeij07 [P100 vs RTX & T4] |
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| ==== P100 vs RTX & T4 ==== | ==== P100 vs RTX 6000 & T4 ==== |
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| The specifications of these GPU models are detailed at this page [[cluster:181|2019 GPU Models]] | The specifications of these GPU models are detailed at this page [[cluster:181|2019 GPU Models]] |
| [[http://www.microway.com|Microway]] | [[http://www.microway.com|Microway]] |
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| First though... | First though...mixed precision calculations are on the rise, driven by Deep Learning. Obviously thwe researcher needs to evaluated if veering away from double precision calculations is scientifically sound. [[https://www.hpcwire.com/2019/08/05/llnl-purdue-researchers-harness-gpu-mixed-precision-for-accuracy-performance-tradeoff/|GPUmixer: harness gpu mixed precision]] |
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| ==== the DPP ==== | ==== the DPP ==== |
| [[https://en.wikipedia.org/wiki/List_of_Nvidia_graphics_processing_units|List of Nvidia Graphics Processing Units]] | [[https://en.wikipedia.org/wiki/List_of_Nvidia_graphics_processing_units|List of Nvidia Graphics Processing Units]] |
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| "Every GPU with SM 1.3 (Tesla/GTX2xx) or better has hardware double-precision support. Starting with the Fermi architecture, Quadro and Tesla variants have better double-precision support than consumer Ge Force models." So I'm utterly confused by this outcome. The P100 is best at double precision (fp64), the RXT6000 is modest and the T4 actually has no specs regarding fp64. Running a colloid example in Lammps compiled for these GPUs with DOUBLE_DOUBLE, all three models obtain the same result in 500,000 loops. Must have something to do with the tensor cores in the T4. | "Every GPU with SM 1.3 (Tesla/GTX2xx) or better has hardware double-precision support. Starting with the Fermi architecture, Quadro and Tesla variants have better double-precision support than consumer Ge Force models." So I'm utterly confused by this outcome. The P100 is best at double precision (fp64), the RXT6000 is modest and the T4 actually has no specs regarding fp64. Running a colloid example in Lammps compiled for these GPUs with DOUBLE_DOUBLE, all three models obtain the same result in 500,000 loops. |
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| | The explanation was found [[https://www.microway.com/hpc-tech-tips/nvidia-turing-tesla-t4-hpc-performance-benchmarks/|T4 benchmarks fp64 and fp32]]. The T4 can do double precision if needed but it's strength is mixed and single precision. |
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| <code> | <code> |
