high performance computing on graphics processing units: hgpu.org

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Fastrack: Fast IO for Secure ML using GPU TEEs

Yongqin Wang, Rachit Rajat, Jonghyun Lee, Tingting Tang, Murali Annavaram

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Tags: Cloud, Computer science, CUDA, Machine learning, nVidia, nVidia H100, Security

October 27, 2024 by hgpu

General-Purpose Computing on Tensor Processors

Kuan-Chieh Hsu

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Tags: Artificial intelligence, Computer science, CUDA, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce RTX 2080, nVidia GeForce RTX 3090, nVidia Jetson Nano, Package, Sparse matrix, Thesis, TPU

October 27, 2024 by hgpu

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

Reza Abbasi, Sernam Lim

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Tags: AI, Artificial intelligence, Computer science, CUDA, LLM, Machine learning, Memory, nVidia, nVidia GeForce RTX 3090, nVidia Quadro RTX 8000, Package

October 20, 2024 by hgpu

Efficient Configuration of Heterogeneous Resources and Task Scheduling Strategies in Deep Learning Auto-Tuning Systems

Pao-Yi Ken, Chao-Chin Wu

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Tags: AI, Artificial intelligence, Computer science, Deep learning, Machine learning, nVidia, nVidia RTX A6000, Task scheduling

October 20, 2024 by hgpu

Deep Learning and Machine Learning with GPGPU and CUDA: Unlocking the Power of Parallel Computing

Ming Li, Ziqian Bi, Tianyang Wang, Yizhu Wen, Qian Niu, Junyu Liu, Benji Peng, Sen Zhang, Xuanhe Pan, Jiawei Xu, Jinlang Wang, Keyu Chen, Caitlyn Heqi Yin, Pohsun Feng, Ming Liu

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Tags: Book, Computer science, CUDA, Deep learning, FPGA, Machine learning, nVidia, OpenCL, OpenGL, TPU, Vulkan

October 13, 2024 by hgpu

Understanding Data Movement in AMD Multi-GPU Systems with Infinity Fabric

Gabin Schieffer, Ruimin Shi, Stefano Markidis, Andreas Herten, Jennifer Faj, Ivy Peng

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Tags: AMD, AMD Radeon Instinct MI250X, ATI, Computer science, HIP, Machine learning, Memory, Performance

October 6, 2024 by hgpu

Evaluating Operators in Deep Neural Networks for Improving Performance Portability of SYCL

Zheming Jin

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Tags: Benchmarking, Computer science, CUDA, HIP, Machine learning, Neural networks, nVidia, nVidia GeForce RTX 2080, nVidia GeForce RTX 3090, nVidia H100, oneAPI, Performance, performance portability, SYCL, Tesla A100, Tesla V100

August 14, 2024 by hgpu

Efficiently Training 7B LLM with 1 Million Sequence Length on 8 GPUs

Pinxue Zhao, Hailin Zhang, Fangcheng Fu, Xiaonan Nie, Qibin Liu, Fang Yang, Yuanbo Peng, Dian Jiao, Shuaipeng Li, Jinbao Xue, Yangyu Tao, Bin Cui

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Tags: AI, Computer science, CUDA, LLM, Machine learning, NLP, nVidia, nVidia A800

July 28, 2024 by hgpu

CATBench: A Compiler Autotuning Benchmarking Suite for Black-box Optimization

Jacob O. Tørring, Carl Hvarfner, Luigi Nardi, Magnus Själander

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Tags: Benchmarking, Compilers, Computer science, Machine learning, nVidia, nVidia GeForce GTX Titan V, nVidia Titan RTX, OpenCL, Package

June 30, 2024 by hgpu

COOK Access Control on an embedded Volta GPU

Benjamin Lesage, Frédéric Boniol, Claire Pagetti

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Tags: Computer science, CUDA, Machine learning, Neural networks, nVidia, nVidia Jetson AGX Xavier

June 23, 2024 by hgpu

Fast and Practical Strassen’s Matrix Multiplication using FPGAs

Afzal Ahmad, Linfeng Du, Wei Zhang

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Tags: BLAS, Computer science, FPGA, GEMM, Linear Algebra, Machine learning, Matrix multiplication, OpenCL, Package

June 9, 2024 by hgpu

SCALE-Ahead-Of-Time Compilation of CUDA for AMD GPUs

LeetDecoding: A PyTorch Library for Exponentially Decaying Causal Linear Attention with CUDA Implementations

Anari-visionaray

Data Parallel Visualization and Rendering on the RAMSES Supercomputer with ANARI

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

Enhancing Deployment-Time Predictive Model Robustness for Code Analysis and Optimization

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

Scalable Access-Pattern Aware I/O Acceleration and Multi-Tiered Data Management for HPC and AI Workloads

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high performance computing on graphics processing units: hgpu.org

General-Purpose Computing on Tensor Processors

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

Efficient Configuration of Heterogeneous Resources and Task Scheduling Strategies in Deep Learning Auto-Tuning Systems

Deep Learning and Machine Learning with GPGPU and CUDA: Unlocking the Power of Parallel Computing

Understanding Data Movement in AMD Multi-GPU Systems with Infinity Fabric

Evaluating Operators in Deep Neural Networks for Improving Performance Portability of SYCL

Efficiently Training 7B LLM with 1 Million Sequence Length on 8 GPUs

CATBench: A Compiler Autotuning Benchmarking Suite for Black-box Optimization

COOK Access Control on an embedded Volta GPU

Fast and Practical Strassen’s Matrix Multiplication using FPGAs

Recent source codes

SCALE-Ahead-Of-Time Compilation of CUDA for AMD GPUs

LeetDecoding: A PyTorch Library for Exponentially Decaying Causal Linear Attention with CUDA Implementations

Anari-visionaray

PROM: an open-source software framework to enhance the robustness and performance of predictive models against such changes during deployment

DeepSpeed: a deep learning optimization library that makes distributed training and inference easy, efficient, and effective

HPX: a C++ Standard Library for Concurrency and Parallelism

TorchQC: Quantum Dynamics and Machine Learning

Matrix multiplication using Tensor Cores in CUDA

CPP Joules: Energy Measurement tool for CPP/CUDA programs

HPC-Coder-v2

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