high performance computing on graphics processing units: hgpu.org

Programming

hgpu.org » Programming

Bandicoot: A Templated C++ Library for GPU Linear Algebra

Ryan R. Curtin, Marcus Edel, Conrad Sanderson

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Tags: Computer science, CUDA, Linear Algebra, nVidia, nVidia GeForce RTX 2080 Ti, OpenCL, Package, Programming techniques

August 24, 2025 by hgpu

Fuzz4cuda: Fuzzing Your Nvidia Gpu Libraries Through Debug Interface

Yuhao Zhou, Peng Jia, Jiayong Liu, Ximing Fan

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Tags: Computer science, CUDA, nVidia, nVidia RTX A6000, PTX, Security

August 24, 2025 by hgpu

Profiling Concurrent Vision Inference Workloads on NVIDIA Jetson – Extended

Abhinaba Chakraborty, Wouter Tavernier, Akis Kourtis, Mario Pickavet, Andreas Oikonomakis, Didier Colle

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Tags: Computer science, CUDA, nVidia, nVidia Jetson Nano, nVidia Jetson Orin Nano, Performance

August 24, 2025 by hgpu

The Fused Kernel Library: A C++ API to Develop Highly-Efficient GPU Libraries

Oscar Amoros, Albert Andaluz, Johnny Nunez, Antonio J. Pena

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Tags: Computer science, CUDA, nVidia, nVidia GeForce RTX 4090, Package, Performance

August 17, 2025 by hgpu

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Chris S. Lin, Joyce Qu, Gururaj Saileshwar

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Tags: Computer science, CUDA, Machine learning, nVidia, nVidia RTX A6000, Package, Security

August 17, 2025 by hgpu

Block: Balancing Load in LLM Serving with Context, Knowledge and Predictive Scheduling

Wei Da, Evangelia Kalyvianaki

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Tags: Artificial intelligence, Computer science, CUDA, LLM, nVidia, nVidia A30, Package, Task scheduling

August 17, 2025 by hgpu

Performant Unified GPU Kernels for Portable Singular Value Computation Across Hardware and Precision

Evelyne Ringoot, Rabab Alomairy, Valentin Churavy, Alan Edelman

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Tags: AMD Radeon Instinct MI250, Apple M1 Pro, ATI, Computer science, HIP, Intel, Intel Ponte Vecchio Max 1100, Kokkos, Linear Algebra, Machine learning, nVidia, nVidia A100, nVidia GeForce RTX 4060, nVidia H100, OpenCL, SYCL

August 17, 2025 by hgpu

ConTraPh: Contrastive Learning for Parallelization and Performance Optimization

Quazi Ishtiaque Mahmud, Ali TehraniJamsaz, Nesreen K. Ahmed, Theodore L. Willke, Ali Jannesari

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Tags: Code generation, Computer science, Heterogeneous systems, HPC, LLM, nVidia, OpenACC, OpenCL, OpenMP, Tesla V100

August 10, 2025 by hgpu

SIGMo: High-Throughput Batched Subgraph Isomorphism on GPUs for Molecular Matching

Antonio De Caro, Gennaro Cordasco, Federico Ficarelli, Biagio Cosenza

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Tags: Biology, Chemistry, Computer science, CUDA, MPI, nVidia, nVidia V100, oneAPI, Package

August 10, 2025 by hgpu

OpenDwarfs 2025: Modernizing the OpenDwarfs Benchmark Suite for Heterogeneous Computing

Juan José Ropero, Manuel de Castro, Diego R. Llanos

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Tags: AMD FirePro W7800, ATI, Benchmarking, Computer science, Heterogeneous systems, nVidia, nVidia RTX 4500 Ada, OpenCL, Package

August 3, 2025 by hgpu

Performance Portable Gradient Computations Using Source Transformation

Kim Liegeois, Brian Kelley, Eric Phipps, Sivasankaran Rajamanickam, Vassil Vassilev

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Tags: AMD Radeon Instinct MI300X, ATI, Computer science, CUDA, HIP, Kokkos, Machine learning, Mathematical Software, nVidia, nVidia H100

August 3, 2025 by hgpu

Kevin: Multi-Turn RL for Generating CUDA Kernels

Carlo Baronio, Pietro Marsella, Ben Pan, Simon Guo, Silas Alberti

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Tags: Artificial intelligence, Computer science, CUDA, LLM, Machine learning, nVidia, nVidia H100, nVidia H200, Performance

July 20, 2025 by hgpu

CUDAnalyst (CUDA + Analyst)

Towards Feedback-to-Plan Decisions for Self-Evolving LLM Agents in CUDA Kernel Generation

CodegenBench

CodegenBench: Can LLMs Write Efficient Code Across Architectures?

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs

Agentic Code Optimization via Compiler-LLM Cooperation

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

See all packages

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high performance computing on graphics processing units: hgpu.org

Programming

Bandicoot: A Templated C++ Library for GPU Linear Algebra

Fuzz4cuda: Fuzzing Your Nvidia Gpu Libraries Through Debug Interface

Profiling Concurrent Vision Inference Workloads on NVIDIA Jetson – Extended

The Fused Kernel Library: A C++ API to Develop Highly-Efficient GPU Libraries

GPUHammer: Rowhammer Attacks on GPU Memories are Practical

Block: Balancing Load in LLM Serving with Context, Knowledge and Predictive Scheduling

Performant Unified GPU Kernels for Portable Singular Value Computation Across Hardware and Precision

ConTraPh: Contrastive Learning for Parallelization and Performance Optimization

SIGMo: High-Throughput Batched Subgraph Isomorphism on GPUs for Molecular Matching

OpenDwarfs 2025: Modernizing the OpenDwarfs Benchmark Suite for Heterogeneous Computing

Performance Portable Gradient Computations Using Source Transformation

Kevin: Multi-Turn RL for Generating CUDA Kernels

Recent source codes

CUDAnalyst (CUDA + Analyst)

CodegenBench

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CUDA Kernel Fusion Benchmarks

IntelliKit: Agent-first tooling for AMD hardware

DITRON: Distributed Compiler based on Triton for Parallel Systems

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Agentic Code Optimization via Compiler-LLM Cooperation

Device Virtual Machine (DVM)

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

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