high performance computing on graphics processing units: hgpu.org

Martin Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Jozefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dan Mane, Rajat Monga, Sherry Moore, Derek Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda Viegas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, Xiaoqiang Zheng

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Tags: Computer science, Computer vision, CUDA, Deep learning, Heterogeneous systems, Information Retrieval, Machine learning, Neural networks, nVidia, Package, Speech recognition

November 11, 2015 by hgpu

high performance computing on graphics processing units: hgpu.org

Applications

GPU-Based Inverse Rendering With Multi-Objective Particle Swarm Optimization

Fast Neuromimetic Object Recognition using FPGA Outperforms GPU Implementations

GEMMbench: a framework for reproducible and collaborative benchmarking of matrix multiplication

Accelerating Recommender Systems using GPUs

Accelerating Adaptive IDW Interpolation Algorithm on a Single GPU

A Survey Of Techniques for Architecting and Managing Asymmetric Multicore Processors

FIESTA 4: optimized Feynman integral calculations with GPU support

Microlensing Observations Rapid Search for Exoplanets: MORSE code for GPUs

A polyphase filter for many-core architectures

Assembly-Free Structural Dynamics On CPU and GPU

Comparison of parallel sorting algorithms

TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

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

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

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