high performance computing on graphics processing units: hgpu.org

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Helix: Distributed Serving of Large Language Models via Max-Flow on Heterogeneous GPUs

Yixuan Mei, Yonghao Zhuang, Xupeng Miao, Juncheng Yang, Zhihao Jia, Rashmi Vinayak

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Tags: Computer science, GPU cluster, Heterogeneous systems, nVidia, nVidia A100, nVidia V100, Tesla T4

June 9, 2024 by hgpu

An implementation of tensor product patch smoothers on GPU

Cu Cui, Paul Grosse-Bley, Guido Kanschat, Robert Strzodka

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Tags: CUDA, FEM, Finite element method, Mathematics, Numerical Analysis, nVidia, nVidia A100

June 2, 2024 by hgpu

Evaluation of computational and energy performance in matrix multiplication algorithms on CPU and GPU using MKL, cuBLAS and SYCL

L.A. Torres, Carlos J. Barrios H, Yves Denneulin

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Source codes

Tags: Computer science, CUBLAS, CUDA, Linear Algebra, Matrix multiplication, Neural networks, nVidia, nVidia A100, Package, Performance, SYCL

June 2, 2024 by hgpu

Enabling full-speed random access to the entire memory on the A100 GPU

Alden Walker

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Tags: Computer science, nVidia, nVidia A100, Performance, PTX

May 26, 2024 by hgpu

ArchesWeather: An efficient AI weather forecasting model at 1.5° resolution

Guillaume Couairon, Christian Lessig, Anastase Charantonis, Claire Monteleoni

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Tags: Deep learning, Earth and Space Sciences, nVidia, nVidia A100, Weather prediction

May 26, 2024 by hgpu

GPU Implementations for Midsize Integer Addition and Multiplication

Cosmin E. Oancea, Stephen M. Watt

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia A100, Performance, Programming Languages

May 26, 2024 by hgpu

STuning-DL: Model-Driven Autotuning of Sparse GPU Kernels for Deep Learning

Roberto L. Castro, Diego Andrade, Basilio B. Fraguela

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Tags: Auto-Tuning, Computer science, CUDA, Deep learning, Machine learning, nVidia, nVidia A100, Tesla T4

May 26, 2024 by hgpu

Kernel-Centric Optimizations for Deep Neural Networks on GPGPU

Zhaodong Chen

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Tags: Computer science, Computer vision, CUDA, Deep learning, Neural networks, nVidia, nVidia A100, nVidia V100, Thesis

May 26, 2024 by hgpu

Hierarchical Resource Partitioning on Modern GPUs: A Reinforcement Learning Approach

Urvij Saroliya, Eishi Arima, Dai Liu, Martin Schulz

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Tags: Computer science, CUDA, Heterogeneous systems, Machine learning, nVidia, nVidia A100, PC cluster, Task scheduling

May 20, 2024 by hgpu

Direct Numerical Simulation of Turbulence on Heterogenous Computer Systems: Architectures, Algorithms, and Applications

Martin Karp

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Tags: AMD Radeon Instinct MI250X, ATI, cfd, Fluid dynamics, FPGA, Heterogeneous systems, Numerical simulation, nVidia, nVidia A100, nVidia P100, nVidia V100, OpenCL, Spectral elements, Thesis

May 12, 2024 by hgpu

Optimizing Hardware Resource Partitioning and Job Allocations on Modern GPUs under Power Caps

Eishi Arima, Minjoon Kang, Issa Saba, Josef Weidendorfer, Carsten Trinitis, Martin Schulz

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Tags: Computer science, CUDA, Energy-efficient computing, Heterogeneous systems, nVidia, nVidia A100, Performance

May 12, 2024 by hgpu

Porting HPC Applications to AMD Instinct MI300A Using Unified Memory and OpenMP

Suyash Tandon, Leopold Grinberg, Gheorghe-Teodor Bercea, Carlo Bertolli, Mark Olesen, Simone Bnà, Nicholas Malaya

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Tags: AMD Radeon Instinct MI210, AMD Radeon Instinct MI300A, ATI, cfd, Computer science, Fluid dynamics, HPC, nVidia, nVidia A100, nVidia H100, OpenMP

May 5, 2024 by hgpu

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

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

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

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high performance computing on graphics processing units: hgpu.org

Helix: Distributed Serving of Large Language Models via Max-Flow on Heterogeneous GPUs

An implementation of tensor product patch smoothers on GPU

Evaluation of computational and energy performance in matrix multiplication algorithms on CPU and GPU using MKL, cuBLAS and SYCL

Enabling full-speed random access to the entire memory on the A100 GPU

ArchesWeather: An efficient AI weather forecasting model at 1.5° resolution

GPU Implementations for Midsize Integer Addition and Multiplication

STuning-DL: Model-Driven Autotuning of Sparse GPU Kernels for Deep Learning

Kernel-Centric Optimizations for Deep Neural Networks on GPGPU

Hierarchical Resource Partitioning on Modern GPUs: A Reinforcement Learning Approach

Direct Numerical Simulation of Turbulence on Heterogenous Computer Systems: Architectures, Algorithms, and Applications

Optimizing Hardware Resource Partitioning and Job Allocations on Modern GPUs under Power Caps

Porting HPC Applications to AMD Instinct MI300A Using Unified Memory and OpenMP

Recent source codes

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

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

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

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

True 4-Bit Quantized CNN Training on CPU

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

KernelSkill: A Multi-Agent Framework for GPU Kernel Optimization

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