high performance computing on graphics processing units: hgpu.org

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Parallel acceleration of CPU and GPU range queries over large data sets

Mitchell Nelson, Zachary Sorenson, Joseph M. Myre, Jason Sawin, David Chiu

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Tags: Compression, Computer science, CUDA, nVidia, nVidia GeForce GTX 1080

August 9, 2020 by hgpu

PERCH 2.0: Fast and Accurate GPU-based Perception via Search for Object Pose Estimation

Aditya Agarwal, Yupeng Han, Maxim Likhachev

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Tags: Computer science, Computer vision, CUDA, nVidia, nVidia GeForce GTX 1070, Package, Robotics, Tesla P100, Tesla V100

August 9, 2020 by hgpu

AnyHLS: High-Level Synthesis with Partial Evaluation

M. Akif Özkan, Arsène Pérard-Gayot, Richard Membarth, Philipp Slusallek, Roland Leissa, Sebastian Hack, Jürgen Teich, Frank Hannig

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Tags: Computer science, FPGA, HLS, Image processing, OpenCL, Package, Programming Languages

August 9, 2020 by hgpu

Bounds Checking on GPU

Troels Henriksen

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Tags: Computer science, CUDA, Memory, nVidia, nVidia GeForce RTX 2080 Ti, OpenCL, Package, Performance

August 2, 2020 by hgpu

OpenSBLI: Automated code-generation for heterogeneous computing architectures applied to compressible fluid dynamics on structured grids

David J. Lusher, Satya P. Jammy, Neil D. Sandham

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Tags: cfd, Code generation, CUDA, Fluid dynamics, GPU cluster, Heterogeneous systems, Numerical simulation, nVidia, OpenCL, OpenMP, OpenMPI, Package, Python, Tesla P100

August 2, 2020 by hgpu

Deep Learning Application in Plant Stress Imaging: A Review

Zongmei Gao, Zhongwei Luo, Wen Zhang, Zhenzhen Lv, Yanlei Xu

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Tags: Deep learning, Earth and Space Sciences, Machine learning, OpenCL, Review, Sensing

August 2, 2020 by hgpu

Optimizing Block-Sparse Matrix Multiplications on CUDA with TVM

Zijing Gu

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Tags: Computer science, CUDA, Deep learning, Machine learning, Matrix multiplication, nVidia, Package, Sparse matrix, Tesla T4

August 2, 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

Bit-level Parallelization of 3DES Encryption on GPU

Kaan Furkan Altınok, Afşin Peker, Alptekin Temizel

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 1660, nVidia GeForce RTX 2060, Package, Security

July 26, 2020 by hgpu

EDSSA: An Encoder-Decoder Semantic Segmentation Networks Accelerator on OpenCL-Based FPGA Platform

Hongzhi Huang, Yakun Wu, Mengqi Yu, Xuesong Shi, Fei Qiao, Li Luo, Qi Wei, Xinjun Liu

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Tags: Algorithm optimization, Computer science, Computer vision, FPGA, Neural networks, OpenCL

July 26, 2020 by hgpu

UVMBench: A Comprehensive Benchmark Suite for Researching Unified Virtual Memory in GPUs

Yongbin Gu, Wenxuan Wu, Yunfan Li, Lizhong Chen

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Tags: Benchmarking, Computer science, CUDA, Memory, nVidia, nVidia GeForce GTX 1080 Ti, Package, Performance

July 26, 2020 by hgpu

Offload Annotations: Bringing Heterogeneous Computing to Existing Libraries and Workloads

Gina Yuan, Shoumik Palkar, Deepak Narayanan, Matei Zaharia

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Package, Python, Tesla P100

July 19, 2020 by hgpu

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

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

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high performance computing on graphics processing units: hgpu.org

Programming

Parallel acceleration of CPU and GPU range queries over large data sets

PERCH 2.0: Fast and Accurate GPU-based Perception via Search for Object Pose Estimation

AnyHLS: High-Level Synthesis with Partial Evaluation

Bounds Checking on GPU

OpenSBLI: Automated code-generation for heterogeneous computing architectures applied to compressible fluid dynamics on structured grids

Deep Learning Application in Plant Stress Imaging: A Review

Optimizing Block-Sparse Matrix Multiplications on CUDA with TVM

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

Bit-level Parallelization of 3DES Encryption on GPU

EDSSA: An Encoder-Decoder Semantic Segmentation Networks Accelerator on OpenCL-Based FPGA Platform

UVMBench: A Comprehensive Benchmark Suite for Researching Unified Virtual Memory in GPUs

Offload Annotations: Bringing Heterogeneous Computing to Existing Libraries and Workloads

Recent source codes

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

ROCm's implementation of Gromacs

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

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