high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications

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

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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

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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

WiLLM: An Open Wireless LLM Communication System

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

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

June 29, 2025 by hgpu

Survey of HPC in US Research Institutions

Peng Shu, Junhao Chen, Zhengliang Liu, Huaqin Zhao, Xinliang Li, Tianming Liu

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Tags: AI, Computer science, HPC, survey

June 29, 2025 by hgpu

Omniwise: Predicting GPU Kernels Performance with LLMs

Zixian Wang, Cole Ramos, Muhammad A. Awad, Keith Lowery

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Tags: AMD, AMD Radeon Instinct MI250, AMD Radeon Instinct MI300X, Artificial intelligence, Benchmarking, Computer science, LLM, Neural networks, Performance, ROCm

June 29, 2025 by hgpu

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

Kunming Zhang, Hanlong Liao, Guoming Tang

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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

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

June 22, 2025 by hgpu

A CPU+FPGA OpenCL Heterogeneous Computing Platform for Multi-Kernel Pipeline

Yuefei Wang, Wendong Mao, Lang Feng, Jin Sha, Zhongfeng Wang

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Tags: Computer science, FPGA, Heterogeneous systems, OpenCL

June 22, 2025 by hgpu

A First Look at Bugs in LLM Inference Engines

Mugeng Liu, Siqi Zhong, Weichen Bi, Yixuan Zhang, Zhiyang Chen, Zhenpeng Chen, Xuanzhe Liu, Yun Ma

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Tags: AI, Computer science, LLM, Software Engineering

June 22, 2025 by hgpu

Engineering Supercomputing Platforms for Biomolecular Applications

Robert Welch, Charles Laughton, Oliver Henrich, Tom Burnley, Daniel Cole, Alan Real, Sarah Harris, James Gebbie-Rayet

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Tags: AMD Radeon Instinct MI250X, AMD Radeon Instinct MI300X, ATI, Benchmarking, Biology, Biomolecules, Computational biology, CUDA, HPC, Molecular dynamics, nVidia, nVidia A100, nVidia GH200, nVidia H100, Package, Physics, ROCm, Tesla V100

June 22, 2025 by hgpu

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration

Jiaqi Lv, Xufeng He, Yanchen Liu, Xu Dai, Yang Hu, Shouyi Yin

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Tags: AI, Benchmarking, Compilers, Computer science, CUDA, Deep learning, LLM, nVidia, nVidia A100, Package, performance portability

June 15, 2025 by hgpu

GPU Acceleration of SQL Analytics on Compressed Data

Zezhou Huang, Krystian Sakowski, Hans Lehnert, Wei Cui, Carlo Curino, Matteo Interlandi, Marius Dumitru, Rathijit Sen

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Tags: Compression, Computer science, CUDA, Databases, Heterogeneous systems, nVidia, nVidia A100

June 15, 2025 by hgpu

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

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

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

AutoKernel: Autonomous GPU Kernel Optimization via Iterative Agent-Driven Search

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

LLM.Q: Quantized LLM training in pure CUDA/C++

LLMQ: Efficient Lower-Precision LLM Training for Consumer GPUs

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

True 4-Bit Quantized CNN Training on CPU

True 4-Bit Quantized Convolutional Neural Network Training on CPU: Achieving Full-Precision Parity

cuFuzz: A GPU-oriented coverage-guided fuzzer for userland CUDA application

Hunting CUDA Bugs at Scale with cuFuzz

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high performance computing on graphics processing units: hgpu.org

Applications

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

WiLLM: An Open Wireless LLM Communication System

Survey of HPC in US Research Institutions

Omniwise: Predicting GPU Kernels Performance with LLMs

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

A Novel Compiler Transformation for Fast Sparse Matrix Multiplication in GPUs

A CPU+FPGA OpenCL Heterogeneous Computing Platform for Multi-Kernel Pipeline

A First Look at Bugs in LLM Inference Engines

Engineering Supercomputing Platforms for Biomolecular Applications

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration

GPU Acceleration of SQL Analytics on Compressed Data

Recent source codes

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

Agentic Code Optimization via Compiler-LLM Cooperation

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

Device Virtual Machine (DVM)

AutoKernel: Autoresearch for GPU kernels. Give it any PyTorch model, go to sleep, wake up to optimized Triton kernels

Triton-Sanitizer: A Fast and Device-Agnostic Memory Sanitizer for Triton with Rich Diagnostic Context

LLM.Q: Quantized LLM training in pure CUDA/C++

SOL-ExecBench: Speed-of-Light Benchmarking for Real-World GPU Kernels Against Hardware Limits

True 4-Bit Quantized CNN Training on CPU

cuFuzz: A GPU-oriented coverage-guided fuzzer for userland CUDA application

Most viewed papers (last 30 days)