java deep learning algorithms and deep neural networks with gpu acceleration
Zero-knowledge proof acceleration with GPUs for C++ and Rust
Programming accelerated applications with CUDA C/C++, enough to be able to begin work accelerating your own CPU-only applications for performance gains, and for moving into novel computational territo...
#计算机科学#A JavaScript library like PyTorch, with GPU acceleration.
Dissecting the M1's GPU for 3D acceleration
翻译 - 剖析M1的GPU进行3D加速
Python library for Room Impulse Response (RIR) simulation with GPU acceleration
Display-agnostic acceleration of macOS applications using external GPUs.
A hardware acceleration library for compute intensive cryptography 🧊
FPGA and GPU acceleration of LeNet5
🔥 High-performance TensorFlow Lite library for React Native with GPU acceleration
Efficient Spiking Neural Network framework, built on top of PyTorch for GPU acceleration
Compute dense optical flow using TV-L1 algorithm with NVIDIA GPU acceleration.
Radeon Rays is ray intersection acceleration library for hardware and software multiplatforms using CPU and GPU
parallel levelSet code using narrow band methods. GPU acceleration is also included
GPU Acceleration using Thundersnow patches that is based on Mesa-Turnip-KGSL
Deep learning framework realized by Numpy purely, supports for both Dynamic Graph and Static Graph with GPU acceleration
This repository is a version of VINS-Fusion with gpu acceleration. It can run on the Nvidia TX2 in realtime
Repo with instruction about how you can setup Proot / Chroot using Termux and GPU acceleration for Box86, Wine, etc.
On-demand transcoding origin server for live inputs and static files in Go using ffmpeg. Also with NVIDIA GPU hardware acceleration.
Intelligent Storage Acceleration Library