high performance computing on graphics processing units: hgpu.org

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Kokkidio: Fast, expressive, portable code, based on Kokkos and Eigen

Lennart Steffen, Reinhard Hinkelmann

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Tags: AMD Radeon Instinct MI100, ATI, Computer science, Intel, Intel Data Center GPU Max 1550, Linear Algebra, nVidia, nVidia A100, nVidia GeForce GTX Titan V, Package, performance portability

November 17, 2024 by hgpu

LLM-Inference-Bench: Inference Benchmarking of Large Language Models on AI Accelerators

Krishna Teja Chitty-Venkata, Siddhisanket Raskar, Bharat Kale, Farah Ferdaus, Aditya Tanikanti, Ken Raffenetti, Valerie Taylor, Murali Emani, Venkatram Vishwanath

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Tags: AI, AMD Radeon Instinct MI250, AMD Radeon Instinct MI300X, Artificial intelligence, ATI, Benchmarking, Computer science, CUDA, LLM, Machine learning, nVidia, nVidia A100, nVidia GH200, nVidia H100, OpenCL, Performance

November 10, 2024 by hgpu

Over-synchronization in GPU Programs

Ajay Nayak, Arkaprava Basu

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Tags: Computer science, CUDA, nVidia, nVidia A100, nVidia GeForce RTX 3090, Package, Performance, PTX

November 10, 2024 by hgpu

Is the GPU Half-Empty or Half-Full? Practical Scheduling Techniques for LLMs

Ferdi Kossmann, Bruce Fontaine, Daya Khudia, Michael Cafarella, Samuel Madden

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Tags: Computer science, LLM, NLP, nVidia, nVidia A100, nVidia H100, Task scheduling

November 3, 2024 by hgpu

Accelerating Drug Discovery in AutoDock-GPU with Tensor Cores

Gabin Schieffer, Ivy Peng

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Tags: Chemistry, Computer science, CUDA, Macromolecule, molecular docking, nVidia, nVidia A100, nVidia V100, Physics, Tesla T4

October 20, 2024 by hgpu

Optimized Code Generation for Parallel and Polyhedral Loop Nests using MLIR

Arun Thangamani

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Tags: AMD Radeon Instinct Mi50, ATI, Code generation, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia A100, OpenCL, Thesis

October 13, 2024 by hgpu

Event-Based OpenMP Tasks for Time-Sensitive GPU-Accelerated Systems

Cyril Cetre, Chenle Yu, Sara Royuela, Rémi Barrere, Eduardo Quiñones, Damien Gratadour

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Tags: AMD Radeon Instinct MI100, ATI, Computer science, CUDA, HIP, HPC, nVidia, nVidia A100, Performance

October 6, 2024 by hgpu

Automatic Generation of OpenCL Code through Polyhedral Compilation with LLM

Marek Palkowski, Mateusz Gruzewski

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Tags: AMD Radeon RX 6800, ATI, Code generation, Computer science, CUDA, LLM, nVidia, nVidia A100, OpenCL, OpenMP

September 29, 2024 by hgpu

A Study of Performance Programming of CPU, GPU accelerated Computers and SIMD Architecture

Xinyao Yi

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Tags: Computer science, CUDA, Heterogeneous systems, HPC, nVidia, nVidia A100, OpenMP, Performance, Programming techniques

September 22, 2024 by hgpu

DNA sequence alignment: An assignment for OpenMP, MPI, and CUDA/OpenCL

Arturo Gonzalez-Escribano, Diego García-Álvarez, Jesús Cámara

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Tags: Bioinformatics, Biology, CUDA, MPI, nVidia, nVidia A100, nVidia GeForce GTX Titan X, nVidia GeForce RTX 4050, OpenCL, Optimization, Sequence alignment

September 15, 2024 by hgpu

Optimal Workload Placement on Multi-Instance GPUs

Bekir Turkkan, Pavankumar Murali, Pavithra Harsha, Rohan Arora, Gerard Vanloo, Chandra Narayanaswami

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Tags: Benchmarking, Computer science, nVidia, nVidia A100, nVidia H100, Performance

September 15, 2024 by hgpu

Enhancing Code Portability, Problem Scale, and Storage Efficiency in Exascale Applicationsin Exascale Applications

Nigel Tan

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Tags: AMD Radeon Vega VII, ATI, Computer science, CUDA, Heterogeneous systems, HPC, nVidia, nVidia A100, nVidia DGX-A100, nVidia Quadro RTX 5000, OpenMP, OpenMPI, Particle-in-cell methods, performance portability, Tesla V100, Thesis

September 15, 2024 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

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high performance computing on graphics processing units: hgpu.org

Kokkidio: Fast, expressive, portable code, based on Kokkos and Eigen

LLM-Inference-Bench: Inference Benchmarking of Large Language Models on AI Accelerators

Over-synchronization in GPU Programs

Is the GPU Half-Empty or Half-Full? Practical Scheduling Techniques for LLMs

Accelerating Drug Discovery in AutoDock-GPU with Tensor Cores

Optimized Code Generation for Parallel and Polyhedral Loop Nests using MLIR

Event-Based OpenMP Tasks for Time-Sensitive GPU-Accelerated Systems

Automatic Generation of OpenCL Code through Polyhedral Compilation with LLM

A Study of Performance Programming of CPU, GPU accelerated Computers and SIMD Architecture

DNA sequence alignment: An assignment for OpenMP, MPI, and CUDA/OpenCL

Optimal Workload Placement on Multi-Instance GPUs

Enhancing Code Portability, Problem Scale, and Storage Efficiency in Exascale Applicationsin Exascale Applications

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

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