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Tracking Latest Benchmarks of dyGiLa |
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benchmark on supercomputer |
Along the course of development and deploy of dyGiLa, multiple stages of benchmark on computing clusters will be conducted. This page dedicates to track the benchmarks of dyGiLa on different hardwares and their scaling capabilities. Based on what kind and how many computing resources on hand, the statistics of benchmark data may change according to how many resources could be put on benchmark runs.
The following plot shows dyGiLa's strong scaling characteristics on LUMI-G GPGPU partition.
the parallel data streaming engine pario was turned off in this benchmark.
the simulation domain has 2048*2048*2048 = 8.5899 billions sites on uniform lattice.
On each site, there are 18 + 18 + 1 + 3 + 1 = 41 float type numbers, which correspond to 2 complex valued matrix fields, 2 scalar filed and one vector field.
Then the total simulation data is 1.408749 Terabyte. This setup was run on LUMI-G with different number of nodes ranged form 6 to 30.
A LUMI-C run with 64 EPYC milan nodes is presented in same plot.
The programming environment (PE) LUMI/24.03 was used in this benchmark.
This PE provides Cray-spined Clang/17.0.1 compiler, gfx90a driver, ROCm/6.0.3 as well as fine tuned toolchain and building tools.
As to be the LUMI maintaining team suggested PE, it does give a perfect strong scaling as shown in cumulated times plot.
Here the cumulated time means Ǹo. of GCDs * wall time for GPUs runs, while 8192 * wall time for CPU run.
In both plots, x-axis stands for the number of Graphics Compute Dies (GCDs) in a run. AMD MI250x has two GCDs per card, then one LUMI-G node has eight GCDs. The blue dots and brown diamonds are simulation time data and measurement data respectively. They are raw data out of simulations. Because the numerical system, which was used for these benchmark runs, are very large, one could expect that the jobs will not be finished in a give time limit such as a day if the hardware resources provided to these runs are not enough. These runs are represented with red dots, of which the simulation time were calculated based on how many simulations have been done in log files. Besides this un-perfect, one still can conclude that dyGiLa does has perfect strong scaling feature by looking these plots.