Modern CUDA Learn Notes with PyTorch for Beginners, 200+ CUDA Kernels, Tensor Cores, HGEMM, FA-2 MMA.
CUDA Core Compute Libraries
A curated list of best cuda programming books
μ-Cuda, COVER THE LAST MILE OF CUDA. With features: intellisense-friendly, structured launch, automatic cuda graph generation and updating.
A dynamic binary instrumentation tool for tracing and analyzing CUDA kernel instructions.
Suckless no dependencies CUDA/C++ port of NVIDIA's DVLT, feed it images, get a 3D point cloud + camera poses. NO python. One fast 5MB binary.
Efficient implementations of Merge Sort and Bitonic Sort algorithms using CUDA for GPU parallel processing, resulting in accelerated sorting of large arrays. Includes both CPU and GPU versions, along with a performance comparison.
A beginner's guide to CUDA programming
An implementation deepdive of scan algorithms in CUDA C++
A C++ header-only library for parallel linear algebra on GPUs (CUDA/cuBLAS under the hood)
learning to develop lightning fast C++/CUDA neural network
基于TensorN和CUDA算子加速的生成式预训练Transformer（GPT）语言模型的C++从零实现
原生C++/CUDA/OpenBLAS实现的张量加速计算库。性能碾压torch（原生CUDA算子实现+0拷贝优化），且更加方便部署。
CUDA C++ repository demonstrating advanced GPU computing, optimized parallel algorithms (FFTs, Tiled MatMul), and NVIDIA ecosystem integrations (cuBLAS, Thrust). Engineered for maximum throughput and HPC learning.
Auditable, fail-closed, fuzz-tested GPU decompression in CUDA C++ — LZ4 batch-decoded on NVIDIA GPUs today; Snappy, GDeflate, and Zstd planned.
Reconstruct 3D point clouds from images using this zero-dependency CUDA inference engine for the DVLT model.
High-performance C++20 Clang LibTooling static analyzer and compiler-driver diagnostics tool for CUDA C++. Detects concurrency, launch, and memory bugs.
This repo contains some CUDA C++ code examples that demonstrate how to use GPUs for parallel computing. Covering topics such as dynamic parallelization, Optimization, ....etc
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