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FlowPM: Distributed TensorFlow Implementation of the FastPM Cosmological N-body Solver

Chirag Modi, Francois Lanusse, Uros Seljak

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Tags: Astrophysics, Cosmology, CUDA, N-body simulation, nVidia, Package, Physics, TensorFlow, Tesla V100

October 25, 2020 by hgpu

Portable high-order finite element kernels I: Streaming Operations

Noel Chalmers, Tim Warburton

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Tags: AMD, AMD Radeon Instinct MI60, AMD Radeon VII, Computer science, CUDA, FEM, HIP, Mathematical Software, nVidia, nVidia GeForce GTX Titan V, OCCA, Portability, Tesla V100

October 18, 2020 by hgpu

When HLS Meets FPGA HBM: Benchmarking and Bandwidth Optimization

Young-kyu Choi, Yuze Chi, Jie Wang, Licheng Guo, Jason Cong

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Tags: Benchmarking, Computer science, FPGA, HLS, OpenCL, Optimization

October 18, 2020 by hgpu

Performance Analysis of Sparse Matrix-Vector Multiplication (SpMV) on Graphics Processing Units (GPUs)

Sarah AlAhmadi, Thaha Mohammed, Aiiad Albeshri, Iyad Katib, Rashid Mehmood

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Tags: Computer science, Heterogeneous systems, HPC, Sparse matrix

October 18, 2020 by hgpu

On the performance of a highly-scalable Computational Fluid Dynamics code on AMD, ARM and Intel processors

Pablo Ouro, Unai Lopez-Novoa, Martyn Guest

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Tags: ARM, cfd, Fluid dynamics, HPC, Performance

October 18, 2020 by hgpu

A Tensor Compiler for Unified Machine Learning Prediction Serving

Supun Nakandala Karla Saur, Gyeong-In Yu, Konstantinos Karanasos, Carlo Curino, Markus Weimer, Matteo Interlandi

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Tags: Computer science, CUDA, Machine learning, nVidia, Package, Tesla K80, Tesla P100

October 18, 2020 by hgpu

Deep Learning for Digital Asset Limit Order Books

Rakshit Jha, Mattijs De Paepe, Samuel Holt, James West, Shaun Ng

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Tags: Deep learning, Finance, Package, Python

October 11, 2020 by hgpu

Bempp-cl: A fast Python based just-in-time compiling boundary element library

Timo Betcke, Matthew W. Scroggs

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Tags: Computer science, Differential equations, Integral equations, OpenCL, Package, Partial differential equations, PDEs, Python

October 11, 2020 by hgpu

Mastering Atari with Discrete World Models

Danijar Hafner, Timothy Lillicrap, Mohammad Norouzi, Jimmy Ba

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Tags: Artificial intelligence, Computer science, Deep learning, Machine learning, nVidia, Package, Python, TensorFlow, Tesla V100

October 11, 2020 by hgpu

It’s all about data movement: Optimising FPGA data access to boost performance

Nick Brown, David Dolman

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Tags: Computer science, FPGA, HLS, Performance

October 11, 2020 by hgpu

Efficient Inference For Neural Machine Translation

Yi-Te Hsu, Sarthak Garg, Yi-Hsiu Liao, Ilya Chatsviorkin

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Tags: Computer science, NLP, nVidia, Tesla V100

October 11, 2020 by hgpu

Transparent Acceleration of Java-based Deep Learning Engines

Athanasios Stratikopoulos, Mihai-Cristian Olteanu, Ian Vaughan, Zoran Sevarac, Nikos Foutris, Juan Fumero, Christos Kotselidis

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Tags: AMD RX Vega 64, ATI, Computer science, Computer vision, Deep learning, Java, nVidia, nVidia GeForce GTX 1050 Ti, OpenCL, Package

October 4, 2020 by hgpu

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

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

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

Agentic Code Optimization via Compiler-LLM Cooperation

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

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high performance computing on graphics processing units: hgpu.org

Applications

FlowPM: Distributed TensorFlow Implementation of the FastPM Cosmological N-body Solver

Portable high-order finite element kernels I: Streaming Operations

When HLS Meets FPGA HBM: Benchmarking and Bandwidth Optimization

Performance Analysis of Sparse Matrix-Vector Multiplication (SpMV) on Graphics Processing Units (GPUs)

On the performance of a highly-scalable Computational Fluid Dynamics code on AMD, ARM and Intel processors

A Tensor Compiler for Unified Machine Learning Prediction Serving

Deep Learning for Digital Asset Limit Order Books

Bempp-cl: A fast Python based just-in-time compiling boundary element library

Mastering Atari with Discrete World Models

It’s all about data movement: Optimising FPGA data access to boost performance

Efficient Inference For Neural Machine Translation

Transparent Acceleration of Java-based Deep Learning Engines

Recent source codes

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CUDA Kernel Fusion Benchmarks

IntelliKit: Agent-first tooling for AMD hardware

DITRON: Distributed Compiler based on Triton for Parallel Systems

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

MegaTrain: Full Precision Training of 100B+ Parameter Large Language Models on a Single GPU

Device Virtual Machine (DVM)

Agentic Code Optimization via Compiler-LLM Cooperation

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

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