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Explicit caching HYB: a new high-performance SpMV framework on GPGPU

Chong Chen

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Tags: Computer science, CUDA, FEM, Finite element method, nVidia, Package, Sparse matrix, Tesla V100

April 17, 2022 by hgpu

Performance study on GPU offloading techniques using the Gauss matrix inverse algorithm

Yannik Könneker

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Tags: Computer science, CUBLAS, CUDA, Linear Algebra, nVidia, nVidia GeForce GTX 1080, OpenACC, OpenCL, Package, Performance, Tesla V100, Thesis

April 17, 2022 by hgpu

PM4Py-GPU: a High-Performance General-Purpose Library for Process Mining

Alessandro Berti, Minh Phan Nghia, Wil M.P. van der Aalst

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Tags: Computer science, Databases, nVidia, nVidia GeForce RTX 2080, Package, Python

April 17, 2022 by hgpu

Optimizing Performance and Energy Efficiency in Massively Parallel Systems

Raúl Nozal González

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Tags: AMD Radeon RX 5700 XT, ATI, Computer science, Heterogeneous systems, HPC, nVidia, nVidia GeForce GTX 950, nVidia GeForce GTX Titan X, OpenCL, Package, Performance, SYCL, Tesla K20, Thesis

April 10, 2022 by hgpu

Performance Models for Heterogeneous Iterative Programs

Aparna Sasidharan

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Performance, Tesla V100

April 10, 2022 by hgpu

Persistent Kernels for Iterative Memory-bound GPU Applications

Lingqi Zhang, Mohamed Wahib, Peng Chen, Jintao Meng, Xiao Wang, Satoshi Matsuoka

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Tags: Computer science, CUDA, nVidia, Package, Stencil computation, Tesla A100, Tesla V100

April 10, 2022 by hgpu

ALPINIST: An Annotation-Aware GPU Program Optimizer

Ömer Sakar, Mohsen Safari, Marieke Huisman, Anton Wijs

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Tags: Computer science, CUDA, nVidia, OpenCL, Optimization, Package

April 10, 2022 by hgpu

Advanced Joins on GPUs

Christos Bellas

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Tags: Algorithms, Computer science, CUDA, Matrix multiplication, nVidia, nVidia GeForce GTX Titan XP, Package, Thesis

March 27, 2022 by hgpu

One-shot tuner for deep learning compilers

Jaehun Ryu, Eunhyeok Park, Hyojin Sung

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Tags: Compilers, Computer science, CUDA, Deep learning, nVidia, nVidia GeForce GTX 2080 Ti, Package

March 27, 2022 by hgpu

Data transfer optimizations for heterogeneous managed runtime systems

Florin-Gabriel Blanaru

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Tags: Computer science, CUDA, Heterogeneous systems, Java, nVidia, nVidia GeForce GTX 1650, nVidia Quadro GP100, OpenCL

March 27, 2022 by hgpu

Migrating CUDA to oneAPI: A Smith-Waterman Case Study

Manuel Costanzo, Enzo Rucci, Carlos Garcia Sanchez, Marcelo Naiouf, Manuel Prieto-Matias

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Tags: Bioinformatics, Biology, CUDA, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan X, nVidia GeForce RTX 2070, Sequence alignment, Smith-Waterman algorithm, SYCL

March 27, 2022 by hgpu

Machine Learning for CUDA+MPI Design Rules

Carl Pearson, Aurya Javeed, Karen Devine

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Tags: Computer science, CUDA, Machine learning, Monte Carlo simulation, MPI, nVidia, nVidia A100

March 20, 2022 by hgpu

CUDA Agent: Large-Scale Agentic RL for High-Performance CUDA Kernel Generation

CUDABench: Benchmarking LLMs for Text-to-CUDA Generation

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Dr. Kernel: Reinforcement Learning Done Right for Triton Kernel Generations

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high performance computing on graphics processing units: hgpu.org

Explicit caching HYB: a new high-performance SpMV framework on GPGPU

Performance study on GPU offloading techniques using the Gauss matrix inverse algorithm

PM4Py-GPU: a High-Performance General-Purpose Library for Process Mining

Optimizing Performance and Energy Efficiency in Massively Parallel Systems

Performance Models for Heterogeneous Iterative Programs

Persistent Kernels for Iterative Memory-bound GPU Applications

ALPINIST: An Annotation-Aware GPU Program Optimizer

Advanced Joins on GPUs

One-shot tuner for deep learning compilers

Data transfer optimizations for heterogeneous managed runtime systems

Migrating CUDA to oneAPI: A Smith-Waterman Case Study

Machine Learning for CUDA+MPI Design Rules

Recent source codes

CUDA Agent: Large-Scale Agentic RL for High-Performance CUDA Kernel Generation

CUDABench: Benchmarking LLMs for Text-to-CUDA Generation

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Vortex-Optimized Light-weight Toolchain (VOLT)

SciDef: Automated Definition Extraction from Scientific Literature

bioagent-bench: Benchmark for evaluating LLM agents in bioinformatics

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