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--- cluster:182 [2019/08/07 12:53]
hmeij07 [P100 vs RTX & T4]
+++ cluster:182 [2019/08/07 18:19]
hmeij07 [P100 vs RTX & T4]
@@ Line 8: / Line 8: @@
 This page will mimic the work done on this page in 2018 [[cluster:175|P100 vs GTX & K20]]
+Credits: This work was made possible, in part, through HPC time donated by Microway, Inc. We gratefully acknowledge Microway for providing access to their GPU-accelerated compute cluster.
+[[http://www.microway.com|Microway]]
 First though...
@@ Line 21: / Line 24: @@
 "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.
 <code>
 p100-dd-1-1:Device 0: Tesla P100-PCIE-16GB, 56 CUs, 16/16 GB, 1.3 GHZ (Double Precision)
@@ Line 35: / Line 38: @@
 t4-dd-1-1:Performance: 518164.721 tau/day, 1199.455 timesteps/s
-<code>
+</code>
 \\
 **[[cluster:0|Back]]**

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