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https://github.com/cea-hpc/HARP
Small tool for profiling the performance of hardware-accelerated Rust code using OpenCL and CUDA
https://github.com/cea-hpc/HARP
cuda gpgpu-computing hpc opencl rust
Last synced: 2 months ago
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Small tool for profiling the performance of hardware-accelerated Rust code using OpenCL and CUDA
- Host: GitHub
- URL: https://github.com/cea-hpc/HARP
- Owner: cea-hpc
- License: apache-2.0
- Created: 2023-04-14T08:41:44.000Z (almost 2 years ago)
- Default Branch: master
- Last Pushed: 2023-08-31T14:15:30.000Z (over 1 year ago)
- Last Synced: 2024-10-15T00:16:26.917Z (4 months ago)
- Topics: cuda, gpgpu-computing, hpc, opencl, rust
- Language: Rust
- Homepage:
- Size: 1.39 MB
- Stars: 9
- Watchers: 9
- Forks: 1
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE-APACHE
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README
# HARP - Hardware-Accelerated Rust Profiling
## About
HARP is a simple profiler for evaluating the performance of hardware-accelerated Rust code. It aims at gauging the capabilities of Rust as a first-class language for GPGPU computing, especially in the field of High Performance Computing (HPC).
Currently, HARP can profile the following GPU-accelerated kernels (targeting OpenCL C and NVIDIA CUDA C++ implementations):
- AXPY (general vector-vector addition)
- GEMM (general dense matrix-matrix multiplication)
- Reduce (32-bit integer sum reduction)
- Scan (32-bit integer sum exclusive scan)
Profiling can be done on both single-precision and double-precision floating-point formats (see [IEEE 754](https://en.wikipedia.org/wiki/IEEE_754)). The `reduce` and `scan` kernels are only supported using 32-bit signed integers for the moment.
## Quickstart
### Pre-requisites
Before starting, make sure the following software is installed on your machine:
- [Rust](https://rustup.rs/) 1.68.0+
- [OpenCL](https://www.khronos.org/opencl/) 2.0+
- [NVIDIA CUDA Toolkit](https://developer.nvidia.com/cuda-downloads) 11.2+ (12.0 recommended) and the appropriate drivers
- ensure the `libnvvm` library is installed and that its path is in the `LD_LIBRARY_PATH` environment variable
- `libnvvm` specifically requires LLVM 7.x (7.0 to 7.4), which you can get [here](https://github.com/llvm/llvm-project/releases/tag/llvmorg-7.1.0)
- [Python](https://www.python.org/downloads/) 3.7+ (only needed for plot generation)
- depends on the `pandas`, `plotly` and `kaleido` Python packages
### Build
First, clone this repository locally:
```sh
git clone https://github.com/cea-hpc/HARP
cd HARP
```
As any Rust-based project, HARP is built with `cargo`:
```sh
cargo build --release
```
### Run
See HARP's documentation for the full list of supported flags, or use the `help` subcommand.
**Example**: to execute HARP and profile a DGEMM on multiple matrix sizes, execute the following example command:
```sh
cargo run --release -- dgemm --sizes 32 64 128 256 512 1024 2048 4096
# Or with shortand aliases
cargo r -r -- dgemm -s 32 64 128 256 512 1024 2048 4096
```
### Documentation
The crate's documentation is available using `cargo`:
```sh
cargo doc --open
```
## Contributing
Contributions are welcome and accepted as pull requests on [GitHub](https://github.com/cea-hpc/HARP).
You may also ask questions or file bug reports on the [issue tracker](https://github.com/cea-hpc/HARP/issues).
## License
Licensed under either of:
- Apache License, Version 2.0 ([LICENSE-APACHE](https://github.com/cea-hpc/HARP/blob/master/LICENSE-APACHE) or [https://www.apache.org/licenses/LICENSE-2.0](https://www.apache.org/licenses/LICENSE-2.0));
- MIT License ([LICENSE-MIT](https://github.com/cea-hpc/HARP/blob/master/LICENSE-MIT) or [http://opensource.org/licenses/MIT](http://opensource.org/licenses/MIT))
at your option.
The [SPDX](https://spdx.dev/) license identifier for this project is MIT OR Apache-2.0.
Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.