high performance computing on graphics processing units: hgpu.org

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Demystifying Dependency Bugs in Deep Learning Stack

Kaifeng Huang, Bihuan Chen, Susheng Wu, Junmin Cao, Lei Ma, Xin Peng

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Tags: Computer science, CUDA, Deep learning, Heterogeneous systems, nVidia

July 24, 2022 by hgpu

CPU-GPU Layer-Switched Low Latency CNN Inference

Ehsan Aghapour, Dolly Sapra, Andy Pimentel, and Anuj Pathania

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Tags: ARM, Computer science, Heterogeneous systems, Machine learning, Neural networks, OpenCL, Package, SoC

July 24, 2022 by hgpu

FPGA Accelerators on Heterogeneous Systems: An Approach Using High Level Synthesis

María Ángelica Dávila Gúzman

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Tags: Computer science, FPGA, HLS, nVidia, nVidia GeForce GTX Titan X, OpenCL, Package, Thesis

July 24, 2022 by hgpu

Theseus: A Library for Differentiable Nonlinear Optimization

Luis Pineda, Taosha Fan, Maurizio Monge, Shobha Venkataraman, Paloma Sodhi, Ricky Chen, Joseph Ortiz, Daniel DeTone, Austin Wang, Stuart Anderson, Jing Dong, Brandon Amos, Mustafa Mukadam

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Tags: Computer science, CUDA, Deep learning, Nonlinear optimization, nVidia, Package, Tesla V100

July 24, 2022 by hgpu

Reducing Synchronous GPU Memory Transfers: Design and implementation of a Futhark compiler optimisation

Philip Jon Børgesen

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Tags: AMD Radeon Instinct MI100, ATI, Computer science, CUDA, nVidia, nVidia A100, OpenCL, Performance, Thesis

July 17, 2022 by hgpu

Heterogeneous Energy-aware Load Balancing for Industry 4.0 and IoT Environments

Usman Ahmed, Jerry Chun-Wei Lin, Gautam Srivastava

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Tags: Computer science, Heterogeneous systems, IoT, Machine learning, nVidia, nVidia GeForce GTX 760, nVidia GeForce GTX 860, OpenCL

July 17, 2022 by hgpu

Just-in-Time Compilation and Link-Time Optimization for OpenMP Target Offloading

Shilei Tian, Joseph Huber, Barbara Chapman, Johannes Doerfert

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Tags: AMD Radeon Instinct MI100, ATI, Compilers, Computer science, CUDA, nVidia, nVidia A100, OpenCL, OpenMP

July 17, 2022 by hgpu

High Performance Simulation for Scalable Multi-Agent Reinforcement Learning

Jordan Langham-Lopez, Sebastian M. Schmon, Patrick Cannon

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Tags: Computer science, CUDA, Deep learning, nVidia, nVidia A100, nVidia GeForce GTX 1650, Performance

July 17, 2022 by hgpu

Design and Implementation of CNN-FPGA accelerator based on Open Computing Language

Praveena Bai Desavathu, A Ravi Raja, Er. Sipra Patra, Rabinarayan Satpathy, S. John Pimo, Sankararao Majji

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Tags: Algorithms, Computer science, Deep learning, FPGA, Neural networks, OpenCL, Package

July 10, 2022 by hgpu

DarKnight: An Accelerated Framework for Privacy and Integrity Preserving Deep Learning Using Trusted Hardware

Hanieh Hashemi, Yongqin Wang, Murali Annavaram

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Tags: Algorithms, Computer science, Deep learning, Linear Algebra, Machine learning, nVidia, nVidia GeForce GTX 1080 Ti, Security

July 10, 2022 by hgpu

FPGA Implementation of Bluetooth Low Energy Physical Layer with OpenCL

Ganyong Mo

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Tags: DSP, FPGA, OpenCL, Signal processing, Thesis

July 10, 2022 by hgpu

High-Performance GPU-to-CPU Transpilation and Optimization via High-Level Parallel Constructs

William S. Moses, Ivan R. Ivanov, Jens Domke, Toshio Endo, Johannes Doerfert, Oleksandr Zinenko

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Tags: Computer science, CUDA, Deep learning, nVidia, nVidia GeForce RTX 2080 Ti, Package, performance portability, Programming Languages

July 10, 2022 by hgpu

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Dr. Kernel: Reinforcement Learning Done Right for Triton Kernel Generations

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Generating Literature-Driven Scientific Theories at Scale

Nsight Python: a Python kernel profiling interface based on NVIDIA Nsight Tools

Nsight Python: A Python-First Profiling Toolkit for Seamless GPU Kernel Analysis (Tool)

Awesome LLM-Driven Kernel Generation

Towards Automated Kernel Generation in the Era of LLMs

PhysProver: Advancing Automatic Theorem Proving for Physics

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

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high performance computing on graphics processing units: hgpu.org

Programming

Demystifying Dependency Bugs in Deep Learning Stack

CPU-GPU Layer-Switched Low Latency CNN Inference

FPGA Accelerators on Heterogeneous Systems: An Approach Using High Level Synthesis

Theseus: A Library for Differentiable Nonlinear Optimization

Reducing Synchronous GPU Memory Transfers: Design and implementation of a Futhark compiler optimisation

Heterogeneous Energy-aware Load Balancing for Industry 4.0 and IoT Environments

Just-in-Time Compilation and Link-Time Optimization for OpenMP Target Offloading

High Performance Simulation for Scalable Multi-Agent Reinforcement Learning

Design and Implementation of CNN-FPGA accelerator based on Open Computing Language

DarKnight: An Accelerated Framework for Privacy and Integrity Preserving Deep Learning Using Trusted Hardware

FPGA Implementation of Bluetooth Low Energy Physical Layer with OpenCL

High-Performance GPU-to-CPU Transpilation and Optimization via High-Level Parallel Constructs

Recent source codes

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Vortex-Optimized Light-weight Toolchain (VOLT)

SciDef: Automated Definition Extraction from Scientific Literature

bioagent-bench: Benchmark for evaluating LLM agents in bioinformatics

Benchmark suite for LLM inference on NVIDIA consumer GPUs

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Nsight Python: a Python kernel profiling interface based on NVIDIA Nsight Tools

Awesome LLM-Driven Kernel Generation

PhysProver: Advancing Automatic Theorem Proving for Physics

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

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