high performance computing on graphics processing units: hgpu.org

Applications

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Development of a new framework for high performance volunteer computing

Ehab Saleh, B. S. Chandrasekar

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Tags: Computer science, Distributed computing, Heterogeneous computing, HPC

December 29, 2024 by hgpu

Asynchronous-Many-Task Systems: Challenges and Opportunities – Scaling an AMR Astrophysics Code on Exascale machines using Kokkos and HPX

Gregor Daiß, Patrick Diehl, Jiakun Yan, John K. Holmen, Rahulkumar Gayatri, Christoph Junghans, Alexander Straub, Jeff R. Hammond, Dominic Marcello, Miwako Tsuji, Dirk Pflüger, Hartmut Kaiser

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Tags: AMD Radeon Instinct MI100, AMD Radeon Instinct MI250X, Astrophysics, ATI, Computer science, CUDA, Heterogeneous systems, HIP, HPC, nVidia, nVidia A100, Package, performance portability, Physics

December 29, 2024 by hgpu

Utilizing Tensor Cores in Futhark

Kristoffer August Kortbæk, Rune Ejnar Bang Lejbølle

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Tags: Benchmarking, Computer science, CUDA, Heterogeneous systems, High-level Languages, Matrix multiplication, nVidia, nVidia A100, Package, PTX

December 24, 2024 by hgpu

CPPJoules: An Energy Measurement Tool for C++

Shivadharshan S, Akilesh P, Rajrupa Chattaraj, Sridhar Chimalakonda

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Tags: Computer science, CUDA, Energy-efficient computing, nVidia, Package, Software Engineering

December 24, 2024 by hgpu

Accelerating Sparse Graph Neural Networks with Tensor Core Optimization

Ka Wai Wu

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Tags: Computer science, CUDA, Graph, Heterogeneous systems, Neural networks, nVidia, PyTorch, Tesla V100

December 24, 2024 by hgpu

HPC-Coder-V2: Studying Code LLMs Across Low-Resource Parallel Languages

Aman Chaturvedi, Daniel Nichols, Siddharth Singh, Abhinav Bhatele

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Tags: Code generation, Computer science, CUDA, HIP, HPC, LLM, MPI, nVidia, nVidia A100, OpenMP, Package

December 24, 2024 by hgpu

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

Ezhilmathi Krishnasamy, Pascal Bouvry

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Tags: BLAS, Computer science, CUDA, Differential equations, HPC, Linear Algebra, Matrix multiplication, nVidia, nVidia A100, OpenACC, Package, Partial differential equations, PDEs, Performance

December 24, 2024 by hgpu

Analyzing the Performance Portability of SYCL across CPUs, GPUs, and Hybrid Systems with Protein Database Search

Manuel Costanzo, Enzo Rucci, Carlos García-Sánchez, Marcelo Naiouf, Manuel Prieto-Matías

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Tags: AMD Radeon RX 6700 XT, AMD Radeon RX Vega 6, ATI, Bioinformatics, Biology, Computer science, CUDA, Databases, Heterogeneous systems, HPC, Intel, Intel Arc A770, Intel UHD 630, Intel UHD 770, nVidia, nVidia GeForce GTX 1080, nVidia GeForce GTX 980, nVidia GeForce RTX 2070, nVidia GeForce RTX 3070, nVidia GeForce RTX 3090, oneAPI, Package, performance portability, SYCL, Tesla V100

December 15, 2024 by hgpu

Towards Performance-Aware Allocation for Accelerated Machine Learning on GPU-SSD Systems

Ayush Gundawar, Euijun Chung, Hyesoon Kim

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Tags: Computer science, Hardware Architecture, Machine learning, Performance

December 15, 2024 by hgpu

RTCUDB: Building Databases with RT Processors

Xuri Shi, Kai Zhang, X. Sean Wang, Xiaodong Zhang, Rubao Lee

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Tags: Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX Titan X, nVidia GeForce RTX 4090

December 15, 2024 by hgpu

Leveraging the potential of task-based programming with OpenMP task graphs

Chenle Yu

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Tags: Computer science, CUDA, nVidia, nVidia V100, OpenMP, Package, Thesis

December 15, 2024 by hgpu

Deep Learning Model Security: Threats and Defenses

Tianyang Wang, Ziqian Bi, Yichao Zhang, Ming Liu, Weiche Hsieh, Pohsun Feng, Lawrence K.Q. Yan, Yizhu Wen, Benji Peng, Junyu Liu, Keyu Chen, Sen Zhang, Ming Li, Chuanqi Jiang, Xinyuan Song, Junjie Yang, Bowen Jing, Jintao Ren, Junhao Song, Hong-Ming Tseng, Silin Chen, Yunze Wang, Chia Xin Liang, Jiawei Xu, Xuanhe Pan, Jinlang Wang, Qian Niu

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Tags: Computer science, Deep learning, nVidia, PyTorch, Review, Security

December 15, 2024 by hgpu

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high performance computing on graphics processing units: hgpu.org

Applications

Development of a new framework for high performance volunteer computing

Asynchronous-Many-Task Systems: Challenges and Opportunities – Scaling an AMR Astrophysics Code on Exascale machines using Kokkos and HPX

Utilizing Tensor Cores in Futhark

CPPJoules: An Energy Measurement Tool for C++

Accelerating Sparse Graph Neural Networks with Tensor Core Optimization

HPC-Coder-V2: Studying Code LLMs Across Low-Resource Parallel Languages

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

Analyzing the Performance Portability of SYCL across CPUs, GPUs, and Hybrid Systems with Protein Database Search

Towards Performance-Aware Allocation for Accelerated Machine Learning on GPU-SSD Systems

RTCUDB: Building Databases with RT Processors

Leveraging the potential of task-based programming with OpenMP task graphs

Deep Learning Model Security: Threats and Defenses

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)