high performance computing on graphics processing units: hgpu.org

Elham E Khoda, Dylan Rankin, Rafael Teixeira de Lima, Philip Harris, Scott Hauck, Shih-Chieh Hsu, Michael Kagan, Vladimir Loncar, Chaitanya Paikara, Richa Rao, Sioni Summers, Caterina Vernieri, Aaron Wang

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Tags: FPGA, Machine learning, Neural networks, Package, Physics

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

Tensor Computation Based on Heterogeneous Memory

Jiawen Liu

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Tags: Computer science, Heterogeneous systems, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 1080 Ti, OpenCL, Prefetch, Thesis

July 3, 2022 by hgpu

Open-source FPGA-ML codesign for the MLPerf Tiny Benchmark

Hendrik Borras, Giuseppe Di Guglielmo, Javier Duarte, Nicolò Ghielmetti, Ben Hawks, Scott Hauck, Shih-Chieh Hsu, Ryan Kastner, Jason Liang, Andres Meza, Jules Muhizi, Tai Nguyen, Rushil Roy, Nhan Tran, Yaman Umuroglu, Olivia Weng, Aidan Yokuda, Michaela Blott

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Tags: Benchmarking, Computer science, FPGA, Heterogeneous systems, Machine learning, Neural networks, Package

June 26, 2022 by hgpu

FELARE: Fair Scheduling of Machine Learning Applications on Heterogeneous Edge Systems

Ali Mokhtari, Pooyan Jamshidi, Mohsen Amini Salehi

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Tags: Computer science, FPGA, Heterogeneous systems, Machine learning, nVidia, Package, Tesla M60

June 5, 2022 by hgpu

Walle: An End-to-End, General-Purpose, and Large-Scale Production System for Device-Cloud Collaborative Machine Learning

Chengfei Lv, Chaoyue Niu, Renjie Gu, Xiaotang Jiang, Zhaode Wang, Bin Liu, Ziqi Wu, Qiulin Yao, Congyu Huang, Panos Huang, Tao Huang, Hui Shu, Jinde Song, Bin Zou, Peng Lan, Guohuan Xu, Fei Wu, Shaojie Tang, Fan Wu, Guihai Chen

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Tags: Cloud, Computer science, Machine learning, Neural networks, nVidia, nVidia GeForce RTX 2080 Ti, Python

June 5, 2022 by hgpu

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

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high performance computing on graphics processing units: hgpu.org

cuZK: Accelerating Zero-Knowledge Proof with A Faster Parallel Multi-Scalar Multiplication Algorithm on GPUs

Towards making the most of NLP-based device mapping optimization for OpenCL kernels

LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale

Optimization of GPU workloads using natural language processing based on deep learning techniques

CPU-GPU Layer-Switched Low Latency CNN Inference

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

Ultra-low latency recurrent neural network inference on FPGAs for physics applications with hls4ml

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

Tensor Computation Based on Heterogeneous Memory

Open-source FPGA-ML codesign for the MLPerf Tiny Benchmark

FELARE: Fair Scheduling of Machine Learning Applications on Heterogeneous Edge Systems

Recent source codes

Matrix multiplication using Tensor Cores in CUDA

CPP Joules: Energy Measurement tool for CPP/CUDA programs

HPC-Coder-v2

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

tdg-benchs: benchmarks used to test the performance of taskgraph

LLOR: Automatic Repair of OpenMP Programs

Solomon: Simple Off-LOading Macros Orchestrating multiple Notations

CLUEstering: a high-performance density-based clustering library for scientific computing

PyOMP: OpenMP for Python in Numba

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