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APNN-TC: Accelerating Arbitrary Precision Neural Networks on Ampere GPU Tensor Cores

Boyuan Feng, Yuke Wang, Tong Geng, Ang Li, Yufei Ding

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Tags: Algorithms, Computer science, CUDA, Deep learning, Neural networks, nVidia, nVidia GeForce RTX 3090, Package, Precision, Python, Tesla A100

June 27, 2021 by hgpu

GPUAPI: Multi-level Chapel Runtime API for GPUs

Akihiro Hayashi, Sri Raj Paul, Vivek Sarkar

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Tags: Code generation, Computer science, CUDA, Heterogeneous systems, HIP, nVidia, OpenCL, Package, SYCL, Tesla V100

June 20, 2021 by hgpu

Study and evaluation of improved automatic GPU offloading method

Yoji Yamato

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Tags: Computer science, CUDA, FPGA, Heterogeneous systems, nVidia, nVidia Quadro P 4000, OpenACC, OpenCL

June 20, 2021 by hgpu

Benchmarking the Nvidia GPU Lineage: From Early K80 to Modern A100 with Asynchronous Memory Transfers

Martin Svedin, Steven W. D. Chien, Gibson Chikafa, Niclas Jansson, Artur Podobas

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Tags: Benchmarking, Computer science, MPI, nVidia, nVidia GeForce GTX 1050 Ti, nVidia Quadro K 2200, Tesla A100, Tesla K80, Tesla P100, Tesla V100

June 20, 2021 by hgpu

StreamBrain: An HPC Framework for Brain-like Neural Networks on CPUs, GPUs and FPGAs

Artur Podobas, Martin Svedin, Steven W. D. Chien, Ivy B. Peng, Naresh Balaji Ravichandran, Pawel Herman, Anders Lansner, Stefano Markidis

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Tags: Bayesian, Computer science, CUDA, Deep learning, FPGA, HPC, Machine learning, MPI, nVidia, OpenMPI, Package, Tesla A100, Tesla V100

June 20, 2021 by hgpu

Experience Report: Writing A Portable GPU Runtime with OpenMP 5.1

Shilei Tian, Jon Chesterfield, Johannes Doerfert, Barbara Chapman

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Tags: Computer science, CUDA, HIP, LLVM, MPI, nVidia, OpenMP, Portability, Tesla V100

June 20, 2021 by hgpu

DLIO: A Data-Centric Benchmark for Scientific Deep Learning Applications

Hariharan Devarajan, Huihuo Zheng, Anthony Kougkas, Xian-He Sun, Venkatram Vishwanath

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Tags: Benchmarking, Computer science, Deep learning, MPI, Neural networks, Package, TensorFlow

June 6, 2021 by hgpu

Data-Driven Analysis and Design of Vulkan Ray-Tracing Applications using Automatic Instrumentation

David Pankratz

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Tags: Computer science, nVidia, nVidia GeForce GTX 1660 Ti, nVidia GeForce RTX 3080, Rasterization, Raytracing, Rendering, Thesis, Visualization, Vulkan

June 6, 2021 by hgpu

Optimization of Heterogeneous Systems with AI Planning Heuristics and Machine Learning: A Performance and Energy Aware Approach

Suejb Memeti, Sabri Pllana

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Tags: Artificial intelligence, Computer science, Heterogeneous systems, Intel Xeon Phi, Machine learning

June 6, 2021 by hgpu

Exploiting co-execution with oneAPI: heterogeneity from a modern perspective

Raúl Nozal, Jose Luis Bosque

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Tags: Computer science, Heterogeneous systems, Intel UHD 630, load balancing, SYCL

June 6, 2021 by hgpu

Early Experiences Migrating CUDA codes to oneAPI

Manuel Costanzo, Enzo Rucci, Carlos García Sanchez, Marcelo Naiouf

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Tags: Computer science, CUDA, FPGA, Heterogeneous systems, nVidia, nVidia GeForce RTX 2070, Portability, SYCL

June 6, 2021 by hgpu

Using Workload Characterization to Guide High Performance Graph Processing

Mohamed W. Hassan

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Tags: Computer science, FPGA, Heterogeneous systems, HLS, nVidia, OpenCL, Optimization, Tesla K20, Thesis

May 30, 2021 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

See all packages

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high performance computing on graphics processing units: hgpu.org

APNN-TC: Accelerating Arbitrary Precision Neural Networks on Ampere GPU Tensor Cores

GPUAPI: Multi-level Chapel Runtime API for GPUs

Study and evaluation of improved automatic GPU offloading method

Benchmarking the Nvidia GPU Lineage: From Early K80 to Modern A100 with Asynchronous Memory Transfers

StreamBrain: An HPC Framework for Brain-like Neural Networks on CPUs, GPUs and FPGAs

Experience Report: Writing A Portable GPU Runtime with OpenMP 5.1

DLIO: A Data-Centric Benchmark for Scientific Deep Learning Applications

Data-Driven Analysis and Design of Vulkan Ray-Tracing Applications using Automatic Instrumentation

Optimization of Heterogeneous Systems with AI Planning Heuristics and Machine Learning: A Performance and Energy Aware Approach

Exploiting co-execution with oneAPI: heterogeneity from a modern perspective

Early Experiences Migrating CUDA codes to oneAPI

Using Workload Characterization to Guide High Performance Graph Processing

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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