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Research and Development of Porting SYCL on QNX Operating System for High Parallelism

Dengpan Wang

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenCL, Operating systems, PTX, SYCL, Thesis

January 16, 2022 by hgpu

A Compiler Framework for Optimizing Dynamic Parallelism on GPUs

Mhd Ghaith Olabi, Juan Gómez Luna, Onur Mutlu, Wen-mei Hwu, Izzat El Hajj

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Tags: Compilers, Computer science, CUDA, nVidia, Package, Performance, Tesla V100

January 16, 2022 by hgpu

Studying the Potential of Automatic Optimizations in the Intel FPGA SDK for OpenCL

Adel Ejjeh, Vikram Adve, Rob Rutenbar

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Tags: Computer science, Design space exploration, FPGA, HLS, OpenCL

January 16, 2022 by hgpu

Reveal training performance mystery between TensorFlow and PyTorch in the single GPU environment

Hulin Dai, Xuan Peng, Xuanhua Shi, Ligang He, Qian Xiong, Hai Jin

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Tags: Benchmarking, Computer science, CUDA, Deep learning, Neural networks, nVidia, Performance, PyTorch, TensorFlow, Tesla P100

January 9, 2022 by hgpu

Domain-Specific On-Device Object Detection Method

Seongju Kang, Jaegi Hwang, Kwangsue Chung

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Tags: Computer science, Computer vision, CUDA, Neural networks, nVidia, nVidia GeForce RTX 2060

January 9, 2022 by hgpu

Analysis of High Level implementations for Recursive Methods on GPUs

Cheng Cao, Justin Kalloor

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Tags: Computer science, CUDA, DSL, nVidia, nVidia GeForce RTX 3080, OpenGL, Vulkan

January 9, 2022 by hgpu

Dynamic GPU Energy Optimization for Machine Learning Training Workloads

Farui Wang, Weizhe Zhang, Shichao Lai, Meng Hao, Zheng Wang

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Tags: Benchmarking, Computer science, CUDA, Energy-efficient computing, Machine learning, nVidia, nVidia GeForce RTX 3080 Ti, Package

January 9, 2022 by hgpu

CFU Playground: Full-Stack Open-Source Framework for Tiny Machine Learning (tinyML) Acceleration on FPGAs

Shvetank Prakash, Tim Callahan, Joseph Bushagour, Colby Banbury, Alan V. Green, Pete Warden, Tim Ansell, Vijay Janapa Reddi

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Tags: Computer science, Design space exploration, FPGA, Machine learning, Package

January 9, 2022 by hgpu

System-Level Optimization and Code Generation for Graphics Processors using a Domain-Specific Language

Bo Qiao

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Tags: Code generation, Computer science, CUDA, Image processing, Machine learning, nVidia, nVidia GeForce GTX 680, nVidia GeForce RTX 2080, OpenCL, Package, performance portability, Tesla K20, Thesis

January 2, 2022 by hgpu

A Unified FPGA Virtualization Framework for General-Purpose Deep Neural Networks in the Cloud

Shulin Zeng, Guohao Dai, Hanbo Sun, Jun Liu, Shiyao Li, Guangjun Ge, Kai Zhong, Kaiyuan Guo, Yu Wang, Huazhong Yang

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Tags: Cloud, Computer science, CUDA, FPGA, Neural networks, nVidia, Tesla V100, Virtualization

January 2, 2022 by hgpu

A Variant of Concurrent Constraint Programming on GPU

Pierre Talbot, Frederic Pinel, Pascal Bouvry

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Tags: Computer science, CUDA, nVidia, nVidia Quadro RTX 5000, Package, Performance

January 2, 2022 by hgpu

PROGRAML: A Graph-based Program Representation for Data Flow Analysis and Compiler Optimizations

Chris Cummins, Zacharias V. Fisches, Tal Ben-Nun, Torsten Hoefler, Michael O'Boyle, Hugh Leather

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Tags: Compilers, Computer science, Flow analysis, Machine learning, OpenCL, Package, Performance

January 2, 2022 by hgpu

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

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

Optical flow algorithms for SYCL

SYCL in the edge: performance and energy evaluation for heterogeneous acceleration

OpenMP5-Offload-OpenMC-Intel-PVC

Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

Research and Development of Porting SYCL on QNX Operating System for High Parallelism

A Compiler Framework for Optimizing Dynamic Parallelism on GPUs

Studying the Potential of Automatic Optimizations in the Intel FPGA SDK for OpenCL

Reveal training performance mystery between TensorFlow and PyTorch in the single GPU environment

Domain-Specific On-Device Object Detection Method

Analysis of High Level implementations for Recursive Methods on GPUs

Dynamic GPU Energy Optimization for Machine Learning Training Workloads

CFU Playground: Full-Stack Open-Source Framework for Tiny Machine Learning (tinyML) Acceleration on FPGAs

System-Level Optimization and Code Generation for Graphics Processors using a Domain-Specific Language

A Variant of Concurrent Constraint Programming on GPU

PROGRAML: A Graph-based Program Representation for Data Flow Analysis and Compiler Optimizations

Recent source codes

QArray

Celerity: High-level C++ for Accelerator Clusters

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

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

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

Optical flow algorithms for SYCL

OpenMP5-Offload-OpenMC-Intel-PVC

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