kernel_tuner
jiro-nn
Our great sponsors
kernel_tuner | jiro-nn | |
---|---|---|
4 | 2 | |
243 | 118 | |
9.9% | - | |
9.1 | 8.5 | |
4 days ago | 7 months ago | |
Python | Rust | |
Apache License 2.0 | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
kernel_tuner
-
Ask HN: What apps have you created for your own use?
I've created Kernel Tuner (https://github.com/KernelTuner/kernel_tuner) as a small software development tool, because I was writing a lot of CUDA and OpenCL kernels at the time. I didn't want to manually figure out what best thread block dimensions and work division among threads were on every GPU over and over again.
The tool evolved quite a bit since the first versions. I'm also using it for testing GPU code, teaching, and it has become one of the main drivers behind a lot of the research that I do.
-
PhD'ers, what are you working on? What CS topics excite you?
We have an open science policy, so anyone can use our framework yourself to optimize stuff, if you want! The original paper is linked at the bottom of the GitHub page.
-
How to Optimize a CUDA Matmul Kernel for CuBLAS-Like Performance: A Worklog
This is a great post for people who are new to optimizing GPU code.
It is interesting to see that the author got this far without interchanging the innermost loop over k to the outermost loop, as is done in CUTLASS (https://github.com/NVIDIA/cutlass).
As you can see in this blog post the code ends up with a lot of compile-time constants (e.g. BLOCKSIZE, BM, BN, BK, TM, TN) one way to optimize this code further is to use an auto-tuner to find the optimal value for all of these parameters for your GPU and problem size, for example Kernel Tuner (https://github.com/KernelTuner/kernel_tuner)
- Kernel Tuner
jiro-nn
-
Deep Learning in Rust with my own framework focusing on ergonomics
With jiro-nn just rely on auto-complete and keep your sanity while following this King County houses sales regression workflow example using a Deep Neural Network:
- I Added CNNs and GPU support to my Neural Network library made from scratch + speaking about it soon at the Scientific Computing in Rust workshop
What are some alternatives?
halutmatmul - Hashed Lookup Table based Matrix Multiplication (halutmatmul) - Stella Nera accelerator
blaze - A Rustified OpenCL Experience
pyopencl - OpenCL integration for Python, plus shiny features
smartcore - A comprehensive library for machine learning and numerical computing. The library provides a set of tools for linear algebra, numerical computing, optimization, and enables a generic, powerful yet still efficient approach to machine learning.
tf-quant-finance - High-performance TensorFlow library for quantitative finance.
rexcel - A lightweight CSV viewer/editor
arrayfire-python - Python bindings for ArrayFire: A general purpose GPU library.
autograph - Machine Learning Library for Rust
scikit-cuda - Python interface to GPU-powered libraries
pair_adjacent_violators - An implementation of the Pair Adjacent Violators algorithm for isotonic regression in Rust
BlendLuxCore - Blender Integration for LuxCore
dfdx - Deep learning in Rust, with shape checked tensors and neural networks