Neural Networks with Sparse Weights in Rust using GPUs, CPUs, and FPGAs via CUDA, OpenCL, and oneAPI
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Updated
May 18, 2024 - Rust
Neural Networks with Sparse Weights in Rust using GPUs, CPUs, and FPGAs via CUDA, OpenCL, and oneAPI
Tensors and Dynamic neural networks in Python with strong GPU acceleration
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
SciML-Bench Benchmarks for Scientific Machine Learning (SciML), Physics-Informed Machine Learning (PIML), and Scientific AI Performance
SkyPilot: Run LLMs, AI, and Batch jobs on any cloud. Get maximum savings, highest GPU availability, and managed execution—all with a simple interface.
Open deep learning compiler stack for cpu, gpu and specialized accelerators
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
On-device AI across mobile, embedded and edge for PyTorch
A Python package for identifying 42 kinds of animals, training custom models, and estimating distance from camera trap videos
GEOS Simulation Framework
The Triton Inference Server provides an optimized cloud and edge inferencing solution.
Video stabilization using gyroscope data
A Julia package to perform Bifurcation Analysis
Efficient CPU/GPU/Vulkan ML Runtimes for VapourSynth (with built-in support for waifu2x, DPIR, RealESRGANv2/v3, Real-CUGAN, RIFE, SCUNet and more!)
GPU-accelerated, C/C++ neural network library.
A library for accelerating Transformer models on NVIDIA GPUs, including using 8-bit floating point (FP8) precision on Hopper and Ada GPUs, to provide better performance with lower memory utilization in both training and inference.
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