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cluster:182 [2019/08/07 12:54]
hmeij07 [the DPP] |
cluster:182 [2019/08/07 12:55]
hmeij07 [the DPP] |
| "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. Must have something to do with the tensor cores in the T4. |
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| <code> | <code> |
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| p100-dd-1-1:Device 0: Tesla P100-PCIE-16GB, 56 CUs, 16/16 GB, 1.3 GHZ (Double Precision) | p100-dd-1-1:Device 0: Tesla P100-PCIE-16GB, 56 CUs, 16/16 GB, 1.3 GHZ (Double Precision) |
