high performance computing on graphics processing units: hgpu.org

hgpu.org » nVidia

Hardware Compute Partitioning on NVIDIA GPUs for Composable Systems

Joshua Bakita, James H. Anderson

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, nVidia, nVidia GeForce RTX 4090, nVidia RTX 6000 Ada, Package, Task scheduling

July 13, 2025 by hgpu

KIS-S: A GPU-Aware Kubernetes Inference Simulator with RL-Based Auto-Scaling

Guilin Zhang, Wulan Guo, Ziqi Tan, Qiang Guan, Hailong Jiang

View

Download (PDF)

Source codes

Tags: Computer science, nVidia, nVidia GeForce RTX 3080, Package, Task scheduling

July 13, 2025 by hgpu

Demystifying NCCL: An In-depth Analysis of GPU Communication Protocols and Algorithms

Zhiyi Hu, Siyuan Shen, Tommaso Bonato, Sylvain Jeaugey, Cedell Alexander, Eric Spada, Jeff Hammond, Torsten Hoefler

View

Download (PDF)

Tags: Computer science, CUDA, GPU cluster, Network communication, nVidia, nVidia GH200

July 13, 2025 by hgpu

Efficient GPU Implementation of Multi-Precision Integer Division

Aske N. Raahauge, Martin B. Marchioro, Marc I. Løvenskjold

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Extended precision, Futhark, nVidia, nVidia A100, Package, Thesis

July 6, 2025 by hgpu

ParEval-Repo: A Benchmark Suite for Evaluating LLMs with Repository-level HPC Translation Tasks

Joshua H. Davis, Daniel Nichols, Ishan Khillan, Abhinav Bhatele

View

Download (PDF)

Source codes

Tags: Benchmarking, Code generation, Computer science, CUDA, LLM, nVidia, nVidia A100, OpenMP, Package

July 6, 2025 by hgpu

Libra: Synergizing CUDA and Tensor Cores for High-Performance Sparse Matrix Multiplication

Jinliang Shi, Shigang Li, Youxuan Xu, Xueying Wang, Rongtian Fu, Zhi Ma, Tong Wu

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Deep learning, Heterogeneous systems, Matrix multiplication, nVidia, nVidia GeForce RTX 4090, nVidia H100, Package, Sparse matrix

July 6, 2025 by hgpu

Accelerated discovery and design of Fe-Co-Zr magnets with tunable magnetic anisotropy through machine learning and parallel computing

Weiyi Xia, Maxim Moraru, Ying Wai Li, Timothy Liao, James R. Chelikowsky, Cai-Zhuang Wang

View

Download (PDF)

Source codes

Tags: Anisotropy, Computational Physics, Condensed matter, CUDA, Machine learning, Materials Science, Neural networks, nVidia, nVidia A100, Package, Physics

July 6, 2025 by hgpu

WiLLM: An Open Wireless LLM Communication System

Boyi Liu, Yongguang Lu, Jianguo Zhao, Qiang Yang, Wen Wu, Lin Chen, Jagmohan Chauhan, Jun Zhang

View

Download (PDF)

Source codes

Tags: Computer science, LLM, Network communications, nVidia, nVidia GeForce RTX 4090, Package

June 29, 2025 by hgpu

GCStack+GCScaler: Fast and Accurate GPU Performance Analyses Using Fine-Grained Stall Cycle Accounting and Interval Analysis

Hanna Cha, Sungchul Lee, Jounghoo Lee, Yeonan Ha, Joonsung Kim, Youngsok Kim

View

Download (PDF)

Tags: Benchmarking, Computer science, CUDA, Design space exploration, nVidia, nVidia GeForce RTX 3070, Performance

June 29, 2025 by hgpu

No More Shading Languages: Compiling C++ to Vulkan Shaders

H. Devillers, M. Kurtenacker, R. Membarth, S. Lemme, M. Kenzel, Ö. Yazici, P. Slusallek

View

Download (PDF)

Source codes

Tags: 3D Graphics and Realism, AMD Radeon RX 7900 XT, ATI, Compilers, GLSL, nVidia, nVidia GeForce RTX 3050 Ti, nVidia GeForce RTX 4070, Package, Raytracing, Rendering, Vulkan

June 29, 2025 by hgpu

LiteGD: Lightweight and dynamic GPU Dispatching for Large-scale Heterogeneous Clusters

Kunming Zhang, Hanlong Liao, Guoming Tang

View

Download (PDF)

Tags: Computer science, GPU cluster, Heterogeneous systems, Machine learning, nVidia, nVidia A800, nVidia GeForce RTX 4090, nVidia H100, nVidia RTX A6000, nVidia V100

June 22, 2025 by hgpu

A Novel Compiler Transformation for Fast Sparse Matrix Multiplication in GPUs

Hossein Albakri, Kazem Cheshmi

View

Download (PDF)

Tags: Compilers, Computer science, CUBLAS, CUDA, Machine learning, Matrix multiplication, Neural networks, nVidia, nVidia A100, Programming Languages, Sparse matrix

June 22, 2025 by hgpu

AutoPass: Evidence-Guided LLM Agents for Compiler Performance Tuning

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

CUDA Kernel Fusion Benchmarks

Analyzing the Impact of Kernel Fusion on GPU Tensor Operation Performance: A Systematic Performance Study

IntelliKit: Agent-first tooling for AMD hardware

Kerncap: Automated Kernel Extraction and Isolation for AMD GPUs

DITRON: Distributed Compiler based on Triton for Parallel Systems

DITRON: Distributed Multi-level Tiling Compiler for Parallel Tensor Programs

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

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Hardware Compute Partitioning on NVIDIA GPUs for Composable Systems

KIS-S: A GPU-Aware Kubernetes Inference Simulator with RL-Based Auto-Scaling

Demystifying NCCL: An In-depth Analysis of GPU Communication Protocols and Algorithms

Efficient GPU Implementation of Multi-Precision Integer Division

ParEval-Repo: A Benchmark Suite for Evaluating LLMs with Repository-level HPC Translation Tasks

Libra: Synergizing CUDA and Tensor Cores for High-Performance Sparse Matrix Multiplication

Accelerated discovery and design of Fe-Co-Zr magnets with tunable magnetic anisotropy through machine learning and parallel computing

WiLLM: An Open Wireless LLM Communication System

GCStack+GCScaler: Fast and Accurate GPU Performance Analyses Using Fine-Grained Stall Cycle Accounting and Interval Analysis

No More Shading Languages: Compiling C++ to Vulkan Shaders

LiteGD: Lightweight and dynamic GPU Dispatching for Large-scale Heterogeneous Clusters

A Novel Compiler Transformation for Fast Sparse Matrix Multiplication in GPUs

Recent source codes

AutoPass: Evidence-Guided LLM Agents for Compiler Performance Tuning

Probe-and-Refine Tuning of Repository Guidance for AI Coding Agents

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

Most viewed papers (last 30 days)