high performance computing on graphics processing units: hgpu.org

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Performance Analysis and Improvement of Parallel Differential Evolution

Zibin Pan

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Tags: Artificial intelligence, Computer science, CUDA, Differential evolution, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTX 760

January 24, 2021 by hgpu

Compound Word Transformer: Learning to Compose Full-Song Music over Dynamic Directed Hypergraphs

Wen-Yi Hsiao, Jen-Yu Liu, Yin-Cheng Yeh, Yi-Hsuan Yang

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Tags: Artificial intelligence, Computer science, Deep learning, nVidia, nVidia GeForce RTX 2080 Ti, Package

January 10, 2021 by hgpu

Hardware and Software Optimizations for Accelerating Deep Neural Networks: Survey of Current Trends, Challenges, and the Road Ahead

Maurizio Capra, Beatrice Bussolino, Alberto Marchisio, Guido Masera, Maurizio Martina, Muhammad Shafique

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Tags: Artificial intelligence, Benchmarking, Computer science, Computer vision, CUDA, Deep learning, Machine learning, Medicine, Neural networks, nVidia, Tesla V100

December 27, 2020 by hgpu

Directive-Based Data Partitioning and Pipelining and Auto-Tuning for High-Performance GPU Computing

Xuewen Cui

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Tags: Artificial intelligence, Auto-Tuning, Computer science, CUDA, HPC, Machine learning, nVidia, OpenMP, Performance, Tesla K40, Tesla P100, Tesla V100, Thesis

December 20, 2020 by hgpu

Mixed-Precision Embedding Using a Cache

Jie (Amy)Yang, Jianyu Huang, Jongsoo Park, Ping Tak Peter Tang, Andrew Tulloch

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Tags: Artificial intelligence, Computer science, CUDA, Machine learning, Mixed precision, nVidia, Tesla V100

October 25, 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

AIPerf: Automated machine learning as an AI-HPC benchmark

Zhixiang Ren, Yongheng Liu, Tianhui Shi, Lei Xie, Yue Zhou, Jidong Zhai, Youhui Zhang, Yunquan Zhang, Wenguang Chen

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Tags: Algorithms, Artificial intelligence, Benchmarking, Computer science, CUDA, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX 1080 Ti, Package, Tesla V100

August 23, 2020 by hgpu

Darknet on OpenCL: a multi-platform tool for object detection and classification

Piotr Sowa, Jacek Izydorczyk

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Tags: ARM, Artificial intelligence, Benchmarking, Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia Titan RTX, OpenCL, Package

July 26, 2020 by hgpu

Parallelization of the Honeybee Search Algorithm for Object Tracking

Oscar E. Perez-Cham, Cesar Puente, Carlos Soubervielle-Montalvo, Gustavo Olague, Carlos A. Aguirre-Salado, Alberto S. Nuñez-Varela

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Tags: AMD Radeon R9 270, Artificial intelligence, ATI, Computer science, Computer vision, nVidia, nVidia GeForce GTX 1050, OpenCL, Particle swarm optimization

April 5, 2020 by hgpu

SOL: Effortless Device Support for AI Frameworks without Source Code Changes

Nicolas Weber, Felipe Huici

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Tags: Artificial intelligence, Computer science, CUDA, Deep learning, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan V100, nVidia Quadro P 4000, PyTorch

March 29, 2020 by hgpu

An Efficient Hardware Accelerator for Structured Sparse Convolutional Neural Networks on FPGAs

Chaoyang Zhu, Kejie Huang, Shuyuan Yang, Ziqi Zhu, Hejia Zhang, Haibin Shen

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Tags: Artificial intelligence, Computer science, Deep learning, FPGA, Neural networks

January 12, 2020 by hgpu

Benchmarking Deep Learning Models on Jetson TX2

Lucas Pedro Bordignon, Aldo von Wangenheim

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Tags: Artificial intelligence, Benchmarking, Computer science, CUDA, Deep learning, Image recognition, nVidia, nVidia Jetson TX2, Overview, Package, Tutorial

November 24, 2019 by hgpu

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

PyOMP: OpenMP for Python in Numba

PyOMP: Parallel programming for CPUs and GPUs with OpenMP and Python

GPPerf: Energy-Aware GPU Performance Prediction and Optimization Framework

Understanding GEMM Performance and Energy on NVIDIA Ada Lovelace: A Machine Learning-Based Analytical Approach

HiRep

Scaling SU(2) to 1000 GPUs using HiRep

Gaia AVU-GSR

Performance portability via C++ PSTL, SYCL, OpenMP, and HIP: the Gaia AVU-GSR case study

gpuPairHMM: Ultra-fast GPU-based PairHMM for DNA Variant Calling

gpuPairHMM: High-speed Pair-HMM Forward Algorithm for DNA Variant Calling on GPUs

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high performance computing on graphics processing units: hgpu.org

Performance Analysis and Improvement of Parallel Differential Evolution

Compound Word Transformer: Learning to Compose Full-Song Music over Dynamic Directed Hypergraphs

Hardware and Software Optimizations for Accelerating Deep Neural Networks: Survey of Current Trends, Challenges, and the Road Ahead

Directive-Based Data Partitioning and Pipelining and Auto-Tuning for High-Performance GPU Computing

Mixed-Precision Embedding Using a Cache

Mastering Atari with Discrete World Models

AIPerf: Automated machine learning as an AI-HPC benchmark

Darknet on OpenCL: a multi-platform tool for object detection and classification

Parallelization of the Honeybee Search Algorithm for Object Tracking

SOL: Effortless Device Support for AI Frameworks without Source Code Changes

An Efficient Hardware Accelerator for Structured Sparse Convolutional Neural Networks on FPGAs

Benchmarking Deep Learning Models on Jetson TX2

Recent source codes

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

SW#SYCL

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

GPPerf: Energy-Aware GPU Performance Prediction and Optimization Framework

HiRep

Gaia AVU-GSR

gpuPairHMM: Ultra-fast GPU-based PairHMM for DNA Variant Calling

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