Hardware Benchmarking Topic HPC on CPU vs GPU
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Introduction
TUFLOW HPC has the ability to run on both CPU and Nvidia CUDA compatible GPU devices. Both CPU and GPU typically have multiple cores, however, GPU devices can have a large number of cores available which can be used to accelerate the TUFLOW HPC computations. CPU cores are typically faster than GPU cores.
For example an i7-8700 Intel CPU has 6 CPU cores (running at up to 4.7GHz) . By contrast a GeForce GTX 1080ti has a total of 3,584 CUDA cores (running at up to 1.58 GHz). At the time of writing both the i7-8700k and GTX 1080ti are high end desktop components.
Computation Speed
The speed at which TUFLOW HPC can solve depends on more than just the number of cores and processor speed, including; instruction set architecture, microarchitecture, precision of computations. Therefore hardware benchmarks specific to TUFLOW provide the best indication of the relative performance of systems.
See also Floating Point Operations per Second (FLOPS) on wikipedia.
Results
The simulations were conducted on a computer with Intel(R) Core(TM) i7-5960X CPU @ 3.00GHz processor. Hyper-threading was disabled during the test This provides access to 8 physical CPU cores. NVIDIA GeForce GTX 980 GPU card (2048 CUDA cores) was used for the HPC GPU test. The table below presents runtimes for the same TUFLOW HPC model on both CPU and GPU hardware, while the the chart below shows the relative speed-up comparing to the same model run with the TUFLOW Classic solver.
| Classic 20m (min) | HPC 20m (min) | ||||
|---|---|---|---|---|---|
| 1 CPU | 1 CPU | 2 CPU | 3 CPU | 4 CPU | 1 GPU |
| 97.9 | 339.8 | 226.4 | 188.0 | 106.68 | 15.4 |
