This repository contains the code implementing the the adaptive, spatially aware two-phase I/O strategy for particle data and the low overhead multiresolution data layout described in our IPDPS 2021 paper: Adaptive Spatially Aware I/O for Multiresoluton Particle Data Layouts. The scripts used to run the benchmarks are available here.
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The parallel I/O benchmarks were run on Stampede2 using the
Skylake Xeon nodes and Summit. On Stampede2 data was written
to /scratch with a stripe size of 8MB and stripe count of 32.
On Summit data was written to /gpfs. Runs on both machines
are done using a process per-core. The benchmark scripts used
for our library and IOR are available in the scripts repository.
The modified version of ExaMPM's mini-app used to generate the
dam break data sets is available here.
On Stampede2 the following modules were loaded:
git/2.24.1
cmake/3.16.1
TACC
qt5/5.11.2
python3/3.6.1
phdf5/1.10.4
autotools/1.1
xalt/2.8
libfabric/1.7.0
gcc/7.1.0
impi/18.0.2
On Summit the following modules were loaded:
hsi/5.0.2.p5
lsftools/2.0
DefApps
cmake/3.15.2
hdf5/1.10.4
git/2.20.1
xalt/1.2.0
darshan-runtime/3.1.7
gcc/9.1.0
spectrum-mpi/10.3.1.2-20200121
python/3.7.0-anaconda3-5.3.0
For our IOR comparisons we built the latest IOR from Github,
at the time this was commit hash 3562a35.
When building our library we use TBB version 2020u1 and glm
at commit hash efbfecab (now released as 0.9.9.8).
The visualization read benchmarks were performed on a desktop with an i9-9920X CPU and 128GB of RAM running Ubuntu 19.04 (GNU/Linux 5.0.0-38-generic x86_64). The data was read from a 1TB Samsung 970 NVMe drive. The compiler used was gcc 8.3.0