cory-master/BabelStream
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

RAJA Instructions for Spack

Browse Source
This commit is contained in:
Kaan Olgu 2023-06-17 11:37:52 +00:00
parent 178763fd52
commit 61f23698e5
1 changed files with 15 additions and 0 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

15
docs/spack_instructions.md
View File

@ -190,10 +190,25 @@
|-----------| ----------------------------------|
| cuda_arch |- List of supported compute capabilities are provided [here](https://github.com/spack/spack/blob/0f271883831bec6da3fc64c92eb1805c39a9f09a/lib/spack/spack/build_systems/cuda.py#LL19C1-L47C6) <br />- Useful [link](https://arnon.dk/matching-sm-architectures-arch-and-gencode-for-various-nvidia-cards/) for matching CUDA gencodes with NVIDIA architectures|
| CPU_ARCH | This sets the `-tp` (target processor) flag, possible values are: <br /> `px` - Generic x86 Processor <br /> `bulldozer` - AMD Bulldozer processor <br /> `piledriver` - AMD Piledriver processor <br /> `zen` - AMD Zen architecture (Epyc, Ryzen) <br /> `zen2` - AMD Zen 2 architecture (Ryzen 2) <br /> `sandybridge` - Intel SandyBridge processor <br /> `haswell` - Intel Haswell processor <br /> `knl` - Intel Knights Landing processor <br /> `skylake` - Intel Skylake Xeon processor <br /> `host` - Link native version of HPC SDK cpu math library <br /> `native` - Alias for -tp host | `cpu_arch=skylake` |
```shell
# Example 1: For GPU Run
$ spack install babelstream +acc cuda_arch=<70>
# Example 2: For Multicore CPU Run
$ spack install babelstream +acc cpu_arch=<bulldozer>
```
## RAJA
* RAJA implementation requires RAJA source folder to be provided because it builds it from the scratch
| Flag | Definition |
|-----------| ----------------------------------|
| dir | Download the Raja release from github repository and extract the zip file to a directory you want and target this directory with `dir` flag |
| backend | 2 different backend options: <br />- cuda <br />- omp |
|offload| Choose offloading platform `offload= [cpu]/[nvidia]` |
```shell
# Example 1: For CPU offload with backend OMP
$ spack install babelstream +raja offload=cpu backend=omp dir=/home/dir/raja
```