high performance computing on graphics processing units: hgpu.org

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Modernization and Optimization of MPI Codes

Tim Jammer

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Tags: Benchmarking, Computer science, HPC, MPI, OpenMP, Package, Performance, Thesis

February 3, 2025 by hgpu

Profiling Apple Silicon Performance for ML Training

Dahua Feng, Zhiming Xu, Rongxiang Wang, Felix Xiaozhu Lin

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Tags: AI, Apple M2 Max, Apple M2 Pro, Apple M2 Ultra, Computer science, CUDA, Linear Algebra, LLM, Machine learning, nVidia, nVidia GeForce RTX 4090, nVidia GeFroce RTX 2080 Ti, nVidia Quadro RTX 4000, nVidia RTX A6000, Performance, PyTorch

February 3, 2025 by hgpu

Good things come in small packages: Should we adopt Lite-GPUs in AI infrastructure?

Burcu Canakci, Junyi Liu, Xingbo Wu, Nathanaël Cheriere, Paolo Costa, Sergey Legtchenko, Dushyanth Narayanan, Ant Rowstron

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Tags: AI, Computer science, Hardware Architecture

January 27, 2025 by hgpu

Exploring data flow design and vectorization with oneAPI for streaming applications on CPU+GPU

Cristian Campos, Rafael Asenjo, Angeles Navarro

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Tags: Computer science, Data parallelism, Heterogeneous systems, Intel, Intel UHD 770, oneAPI, Package, SYCL

January 27, 2025 by hgpu

Adaptive Optimization Techniques for High-Performance Computing

Gulsum Gudukbay Akbulut

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Tags: Computer science, CUDA, Deep learning, HPC, Machine learning, nVidia, Optimization, Performance, Tesla K80, Thesis

January 27, 2025 by hgpu

Column-Oriented Datalog on the GPU

Yihao Sun, Sidharth Kumar, Thomas Gilray, Kristopher Micinski

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Tags: Computer science, CUDA, Databases, nVidia, nVidia H100, Package

January 27, 2025 by hgpu

Dissecting the NVIDIA Hopper Architecture through Microbenchmarking and Multiple Level Analysis

Weile Luo, Ruibo Fan, Zeyu Li, Dayou Du, Hongyuan Liu, Qiang Wang, Xiaowen Chu

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Tags: Benchmarking, Computer science, CUDA, Hardware Architecture, nVidia, nVidia A100, nVidia GeForce RTX 4090, nVidia H800, Performance, PTX

January 27, 2025 by hgpu

Code Generation for Cryptographic Kernels using Multi-word Modular Arithmetic on GPU

Naifeng Zhang, Franz Franchetti

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Tags: Code generation, Computer science, CUDA, Linear Algebra, Modular arithmetic, nVidia, nVidia GeForce RTX 4090, nVidia H100, nVidia V100, Package, Security

January 20, 2025 by hgpu

GSParLib: A multi-level programming interface unifying OpenCL and CUDA for expressing stream and data parallelism

Dinei A. Rockenbach, Gabriell Araujo, Dalvan Griebler, Luiz Gustavo Fernandes

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Tags: Computer science, CUDA, Data parallelism, nVidia, nVidia GeForce RTX 3090, OpenCL, OpenMP, Package

January 20, 2025 by hgpu

A User’s Guide to KSig: GPU-Accelerated Computation of the Signature Kernel

Csaba Tóth, Danilo Jr Dela Cruz, Harald Oberhauser

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Tags: Computer science, CUDA, Machine learning, nVidia, nVidia A100, Package, Python

January 20, 2025 by hgpu

Boosting Performance of Iterative Applications on GPUs: Kernel Batching with CUDA Graphs

Jonah Ekelund, Stefano Markidis, Ivy Peng

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Tags: Computer science, CUDA, FDTD, HIP, nVidia, nVidia A100, nVidia H100, Package, Performance

January 20, 2025 by hgpu

Keras Sig: Efficient Path Signature Computation on GPU in Keras 3

Rémi Genet, Hugo Inzirillo

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Tags: Computer science, CUDA, Deep learning, Machine learning, nVidia, nVidia GeForce RTX 4090, Package, Python, TensorFlow

January 20, 2025 by hgpu

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

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Generating Literature-Driven Scientific Theories at Scale

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high performance computing on graphics processing units: hgpu.org

Applications

Modernization and Optimization of MPI Codes

Profiling Apple Silicon Performance for ML Training

Good things come in small packages: Should we adopt Lite-GPUs in AI infrastructure?

Exploring data flow design and vectorization with oneAPI for streaming applications on CPU+GPU

Adaptive Optimization Techniques for High-Performance Computing

Column-Oriented Datalog on the GPU

Dissecting the NVIDIA Hopper Architecture through Microbenchmarking and Multiple Level Analysis

Code Generation for Cryptographic Kernels using Multi-word Modular Arithmetic on GPU

GSParLib: A multi-level programming interface unifying OpenCL and CUDA for expressing stream and data parallelism

A User’s Guide to KSig: GPU-Accelerated Computation of the Signature Kernel

Boosting Performance of Iterative Applications on GPUs: Kernel Batching with CUDA Graphs

Keras Sig: Efficient Path Signature Computation on GPU in Keras 3

Recent source codes

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

Benchmark suite for LLM inference on NVIDIA consumer GPUs

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

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