high performance computing on graphics processing units: hgpu.org

Programming

hgpu.org » Programming

MNN: A Universal and Efficient Inference Engine

Xiaotang Jiang, Huan Wang, Yiliu Chen, Ziqi Wu, Lichuan Wang, Bin Zou, Yafeng Yang, Zongyang Cui, Yu Cai, Tianhang Yu, Chengfei Lv, Zhihua Wu

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Tags: Computer science, Deep learning, Neural networks, OpenCL, Package, Vulkan

April 12, 2020 by hgpu

Using Machine Learning to Estimate Utilization and Throughput for OpenCL-Based SpMV Implementation on an FPGA

Jannatun Naher, Clay Gloster, Shrikant S. Jadhav, Christopher C. Doss

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Tags: Computer science, Design space exploration, DSP, FPGA, Linear Algebra, Machine learning, OpenCL, Sparse matrix

April 12, 2020 by hgpu

Open Source Face Recognition API

Diogo Neto Coxinho Mourisco da Conceição

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Tags: Algorithms, Computer science, Computer vision, Databases, Face detection, Package, Python, Thesis

April 12, 2020 by hgpu

Neural Architecture Search for Lightweight Non-Local Networks

Yingwei Li, Xiaojie Jin, Jieru Mei, Xiaochen Lian, Linjie Yang, Cihang Xie, Qihang Yu, Yuyin Zhou, Song Bai, Alan Yuille

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Tags: Algorithms, Computer science, Deep learning, Neural networks, nVidia, Package, TensorFlow, Tesla V100

April 12, 2020 by hgpu

LUDA: Boost LSM Key Value Store Compactions with GPUs

Peng Xu, Jiguang Wan, Ping Huang, Xiaogang Yang, Chenlei Tang, Fei Wu, Changsheng Xie

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Tags: Computer science, CUDA, Databases, nVidia, nVidia GeForce GTX 1080 Ti

April 12, 2020 by hgpu

Deep Learning for Compilers

Chris Cummins

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Tags: AMD Radeon HD 7970, ATI, Benchmarking, Compilers, Computer science, Deep learning, Heterogeneous systems, nVidia, nVidia GeForce GTX 970, OpenCL, Package, Thesis

April 5, 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

PyMatting: A Python Library for Alpha Matting

Thomas Germer, Tobias Uelwer, Stefan Conrad, Stefan Harmeling

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Tags: Computer vision, CUDA, Image processing, nVidia, OpenCL, Package, PyOpenCL, Python

April 5, 2020 by hgpu

Faster than FAST: GPU-Accelerated Frontend for High-Speed VIO

Balazs Nagy, Philipp Foehn, Davide Scaramuzza

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Tags: Algorithms, Computer vision, CUDA, Image processing, nVidia, nVidia GeForce GTX 960 M, nVidia Jetson TX2, OpenCV, Package

April 5, 2020 by hgpu

Understanding GPU-Based Lossy Compression for Extreme-Scale Cosmological Simulations

Sian Jin, Pascal Grosset, Christopher M. Biwer, Jesus Pulido, Jiannan Tian, Dingwen Tao, James Ahrens

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Tags: Astrophysics, Compression, Computational Physics, Cosmology, CUDA, Instrumentation and Methods for Astrophysics, nVidia, nVidia GeForce GTX 1080 Ti, nVidia GeForce GTX Titan V, nVidia GeForce RTX 2080 Ti, nVidia Quadro P 6000, Package, Physics, Tesla K80, Tesla P100, Tesla V100

April 5, 2020 by hgpu

Large-Scale Data Computing Performance Comparisons on SYCL Heterogeneous Parallel Processing Layer Implementations

Woosuk Shin, Kwan-Hee Yoo, Nakhoon Baek

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Tags: Computer science, CUDA, DSL, Heterogeneous systems, nVidia, nVidia GeForce GTX 960, OpenCL, SYCL

March 29, 2020 by hgpu

Characterizing Optimizations to Memory Access Patterns using Architecture-Independent Program Features

Aditya Chilukuri, Josh Milthorpe, Beau Johnston

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Tags: Computer science, Heterogeneous systems, Memory, nVidia, OpenCL, Performance, Tesla P100

March 29, 2020 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

gpu_tracker: Python package for tracking and profiling GPU utilization in both desktop and high-performance computing environments

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

LOOPer: A Learned Automatic Code Optimizer For Polyhedral Compilers

OpenMC Monte Carlo Code

Performance Portable Monte Carlo Particle Transport on Intel, NVIDIA, and AMD GPUs

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

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high performance computing on graphics processing units: hgpu.org

Programming

MNN: A Universal and Efficient Inference Engine

Using Machine Learning to Estimate Utilization and Throughput for OpenCL-Based SpMV Implementation on an FPGA

Open Source Face Recognition API

Neural Architecture Search for Lightweight Non-Local Networks

LUDA: Boost LSM Key Value Store Compactions with GPUs

Deep Learning for Compilers

Parallelization of the Honeybee Search Algorithm for Object Tracking

PyMatting: A Python Library for Alpha Matting

Faster than FAST: GPU-Accelerated Frontend for High-Speed VIO

Understanding GPU-Based Lossy Compression for Extreme-Scale Cosmological Simulations

Large-Scale Data Computing Performance Comparisons on SYCL Heterogeneous Parallel Processing Layer Implementations

Characterizing Optimizations to Memory Access Patterns using Architecture-Independent Program Features

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

LOOPer: a polyhedral compiler for expressing fast and portable data parallel algorithms

OpenMC Monte Carlo Code

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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