high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications

LLOR: Automated Repair of OpenMP Programs

Utpal Bora, Saurabh Joshi, Gautam Muduganti, Ramakrishna Upadrasta

View

Download (PDF)

Source codes

Tags: Computer science, Fortran, OpenMP, Package

December 8, 2024 by hgpu

Automating Energy-Efficient GPU Kernel Generation: A Fast Search-Based Compilation Approach

Yijia Zhang, Zhihong Gou, Shijie Cao, Weigang Feng, Sicheng Zhang, Guohao Dai, Ningyi Xu

View

Download (PDF)

Tags: Computer science, CUDA, Energy-efficient computing, Machine learning, Neural networks, nVidia, nVidia A100, nVidia GeForce RTX 4090, Performance

December 8, 2024 by hgpu

Unified schemes for directive-based GPU offloading

Yohei Miki, Toshihiro Hanawa

View

Download (PDF)

Source codes

Tags: AMD Radeon Instinct MI210, ATI, Computer science, Diffusion equation, Intel, Intel Ponte Vecchio Max 1100, N-body simulation, nVidia, nVidia GH200, nVidia H100, OpenACC, OpenMP, Package

December 8, 2024 by hgpu

FortranX: Harnessing Code Generation, Portability, and Heterogeneity in Fortran

Sanil Rao, Mike Franusich, , Mohammad Alaul Haque Monil, Het Mankad, Jeffrey S. Vetter, Franz Franchetti

View

Download (PDF)

Tags: AMD, ATI, Code generation, Computer science, CUDA, Differential equations, Fortran, Heterogeneous systems, HIP, nVidia, OpenCL, OpenMP, Partial differential equations, PDEs

December 8, 2024 by hgpu

Guardian: Safe GPU Sharing in Multi-Tenant Environments

Manos Pavlidakis, Giorgos Vasiliadis, Anargyros Argyros, Stelios Mavridis, Antony Chazapis, Angelos Bilas

View

Download (PDF)

Tags: Computer science, CUDA, nVidia, nVidia GeForce RTX 3080 Ti, nVidia RTX A4000, PTX, Security

December 8, 2024 by hgpu

CLUEstering: a high-performance density-based clustering library for scientific computing

Simone Balducci

View

Download (PDF)

Source codes

Tags: Astrophysics, ATI, Clustering, CUDA, FPGA, HIP, Machine learning, nVidia, Package, performance portability, Physics, Python, Tesla T4, Thesis

December 1, 2024 by hgpu

PyOMP: Parallel programming for CPUs and GPUs with OpenMP and Python

Giorgis Georgakoudis, Todd A. Anderson, Stuart Archibald, Bronis de Supinski,Timothy G. Mattson

View

Download (PDF)

Source codes

Tags: Benchmarking, Computer science, nVidia, nVidia A100, OpenMP, Package, Python

December 1, 2024 by hgpu

Hardware Accelerators for Artificial Intelligence

S M Mojahidul Ahsan, Anurag Dhungel, Mrittika Chowdhury, Md Sakib Hasan, Tamzidul Hoque

View

Download (PDF)

Tags: AI, Computer science, Hardware Architecture, Performance, survey

December 1, 2024 by hgpu

Scaling SU(2) to 1000 GPUs using HiRep

Sofie Martins, Erik Kjellgren, Emiliano Molinaro, Claudio Pica, Antonio Rago

View

Download (PDF)

Source codes

Tags: AMD Radeon Instinct MI250X, ATI, CUDA, HEP, High Energy Physics - Lattice, HIP, Monte Carlo simulation, nVidia, nVidia H100, Package, Physics

December 1, 2024 by hgpu

Understanding GEMM Performance and Energy on NVIDIA Ada Lovelace: A Machine Learning-Based Analytical Approach

Xiaoteng (Frank) Liu, Pavly Halim

View

Download (PDF)

Source codes

Tags: Computer science, CUDA, Energy-efficient computing, GEMM, Machine learning, Matrix multiplication, nVidia, nVidia GeForce RTX 4070, Package, Performance

December 1, 2024 by hgpu

A Distributed-memory Tridiagonal Solver Based on a Specialised Data Structure Optimised for CPU and GPU Architectures

Semih Akkurt, Sébastien Lemaire, Paul Bartholomew, Sylvain Laizet

View

Download (PDF)

Tags: Computational Physics, Computer science, CUDA, nVidia, nVidia A100, nVidia GH200, nVidia H100, nVidia V100, OpenMP, PDEs

November 24, 2024 by hgpu

SoK: A Systems Perspective on Compound AI Threats and Countermeasures

Sarbartha Banerjee, Prateek Sahu, Mulong Luo, Anjo Vahldiek-Oberwagner, Neeraja J. Yadwadkar, Mohit Tiwari

View

Download (PDF)

Tags: AI, Artificial intelligence, Computer science, LLM, Machine learning, Security

November 24, 2024 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

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Applications

LLOR: Automated Repair of OpenMP Programs

Automating Energy-Efficient GPU Kernel Generation: A Fast Search-Based Compilation Approach

Unified schemes for directive-based GPU offloading

FortranX: Harnessing Code Generation, Portability, and Heterogeneity in Fortran

Guardian: Safe GPU Sharing in Multi-Tenant Environments

CLUEstering: a high-performance density-based clustering library for scientific computing

PyOMP: Parallel programming for CPUs and GPUs with OpenMP and Python

Hardware Accelerators for Artificial Intelligence

Scaling SU(2) to 1000 GPUs using HiRep

Understanding GEMM Performance and Energy on NVIDIA Ada Lovelace: A Machine Learning-Based Analytical Approach

A Distributed-memory Tridiagonal Solver Based on a Specialised Data Structure Optimised for CPU and GPU Architectures

SoK: A Systems Perspective on Compound AI Threats and Countermeasures

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)