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Enhancing the Performance Portability of Heterogeneous Circuit Analysis Programs

Tsung-Wei Huang

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Tags: AMD Radeon RX 6900 XT, ATI, Computer science, Deep learning, nVidia, nVidia GeForce RTX 3090, OpenCL, performance portability, PyTorch, SYCL

September 11, 2022 by hgpu

Lina: a fast design optimisation tool for software-based FPGA programming

Andre Bannwart Perina

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Tags: Computer science, Design space exploration, FPGA, nVidia, nVidia Quadro K620, OpenCL, Package, Thesis

September 4, 2022 by hgpu

GGArray: A Dynamically Growable GPU Array

Enzo meneses, Cristóbal A. Navarro, Héctor Ferrada

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Tags: Algorithms, Computer science, CUDA, Memory, nVidia, nVidia A100, nVidia Titan RTX

September 4, 2022 by hgpu

Towards making the most of NLP-based device mapping optimization for OpenCL kernels

Petros Vavaroutsos, Ioannis Oroutzoglou, Dimosthenis Masouros, Dimitrios Soudris

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Tags: AMD Radeon HD 7970, ATI, Computer science, Deep learning, Machine learning, NLP, nVidia, nVidia GeForce GTX 970, OpenCL

September 4, 2022 by hgpu

Understanding the Power of Evolutionary Computation for GPU Code Optimization

Jhe-Yu Liou, Muaaz Awan, Steven Hofmeyr, Stephanie Forrest, Carole-Jean Wu

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Tags: Bioinformatics, Biology, Computer science, CUDA, Evolutionary Computations, Neural and Evolutionary Computing, nVidia, nVidia GeForce GTX 1080 Ti, Package, performance portability, Sequence alignment, Tesla P100, Tesla V100

September 4, 2022 by hgpu

Towards Understanding and Mitigating Memory-Access Challenges in Computing Systems

Mohammad K. Dashti

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Tags: Computer science, CUDA, Deep learning, Heterogeneous systems, Memory model, nVidia, nVidia GeForce RTX 2070, nVidia Jetson TK1, OpenCL, Package, Thesis

August 28, 2022 by hgpu

Fully Concurrent GPU Data Structures

Muhammad Abdelghaffar Awad

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Tags: Computer science, CUDA, Data Structures and Algorithms, nVidia, nVidia GeForce GTX Titan V, Package, Tesla V100

August 28, 2022 by hgpu

Long Code for Code Search

Fan Hu, Yanlin Wang, Lun Du, Hongyu Zhang, Shi Han, Dongmei Zhang, Xirong Li

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Tags: Computer science, Deep learning, NLP, nVidia, Software Engineering, Tesla V100

August 28, 2022 by hgpu

Demystifying the Nvidia Ampere Architecture through Microbenchmarking and Instruction-level Analysis

Hamdy Abdelkhalik, Yehia Arafa, Nandakishore Santhi, Abdel-Hameed Badawy

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Tags: Benchmarking, Computer science, Hardware Architecture, Latency, nVidia, nVidia A100, Performance, PTX

August 28, 2022 by hgpu

Exploring Thread Coarsening on FPGA

Mostafa Eghbali Zarch, Reece Neff, Michela Becchi

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Tags: Compilers, Computer science, FPGA, OpenCL, Performance, performance portability

August 28, 2022 by hgpu

BenchPress: A Deep Active Benchmark Generator

Foivos Tsimpourlas, Pavlos Petoumenos, Min Xu, Chris Cummins, Kim Hazelwood, Ajitha Rajan, Hugh Leather

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Tags: Benchmarking, Code generation, Computer science, Deep learning, nVidia, nVidia GeForce GTX 1080, OpenCL, Package, PyTorch

August 21, 2022 by hgpu

Performance analysis of matrix-free conjugate gradient kernels using SYCL

Igor Baratta, Chris Richardson, Garth Wells

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Tags: Benchmarking, Computer science, Latency, nVidia, nVidia A100, OpenCL, Package, Performance, SYCL

August 21, 2022 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

Enhancing the Performance Portability of Heterogeneous Circuit Analysis Programs

Lina: a fast design optimisation tool for software-based FPGA programming

GGArray: A Dynamically Growable GPU Array

Towards making the most of NLP-based device mapping optimization for OpenCL kernels

Understanding the Power of Evolutionary Computation for GPU Code Optimization

Towards Understanding and Mitigating Memory-Access Challenges in Computing Systems

Fully Concurrent GPU Data Structures

Long Code for Code Search

Demystifying the Nvidia Ampere Architecture through Microbenchmarking and Instruction-level Analysis

Exploring Thread Coarsening on FPGA

BenchPress: A Deep Active Benchmark Generator

Performance analysis of matrix-free conjugate gradient kernels using SYCL

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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