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Hierarchical Matrix Operations on GPUs: Matrix-Vector Multiplication and Compression

Wajih Halim Boukaram, George Turkiyyah, David E. Keyes

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Tags: Compression, Computer science, CUDA, Linear Algebra, Mathematical Software, nVidia, Tesla P100

February 10, 2019 by hgpu

ThunderGBM: Fast GBDTs and Random Forests on GPUs

Zeyi Wen, Jiashuai Shi, Bingsheng He, Qinbin Li, Jian Chen

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Tags: Computer science, CUDA, Data mining, Machine learning, nVidia, Package, Python, Tesla P100

February 3, 2019 by hgpu

Swizzle Inventor: Data Movement Synthesis for GPU Kernels

Phitchaya Mangpo Phothilimthana, Archibald Samuel Elliott, An Wang, Abhinav Jangda, Bastian Hagedorn, Henrik Barthels, Samuel J. Kaufman, Vinod Grover, Emina Torlak, Rastislav Bodik

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Tags: Code generation, Computer science, CUDA, nVidia, nVidia GeForce GTX Titan X, nVidia Quadro GV100

February 3, 2019 by hgpu

The OoO VLIW JIT Compiler for GPU Inference

Paras Jain, Xiangxi Mo, Ajay Jain, Alexey Tumanov, Joseph E. Gonzalez, Ion Stoica

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Tags: Compilers, Computer science, CUDA, Data parallelism, Machine learning, nVidia, Tesla V100

February 3, 2019 by hgpu

High Performance Algorithms for Counting Collisions and Pairwise Interactions

Matheus Henrique Junqueira Saldanha, Paulo Sérgio Lopes de Souza

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Tags: Collision detection, Computer science, CUDA, nVidia, Package, Tesla P100

February 3, 2019 by hgpu

DeepSZ: A Novel Framework to Compress Deep Neural Networks by Using Error-Bounded Lossy Compression

Sian Jin, Sheng Di, Xin Liang, Jiannan Tian, Dingwen Tao, Franck Cappello

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Tags: Compression, Computer science, Deep learning, Neural networks, nVidia, Performance, Tesla V100

February 3, 2019 by hgpu

Exploiting OpenMP & OpenACC to Accelerate a Molecular Docking Mini-App in Heterogeneous HPC Nodes

Emanuele Vitali, Davide Gadioli, Gianluca Palermo, Andrea Beccari, Carlo Cavazzoni, Cristina Silvano

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Tags: Computer science, CUDA, Heterogeneous systems, HPC, molecular docking, MPI, nVidia, OpenACC, OpenMP, Tesla K80

January 27, 2019 by hgpu

Supporting mixed-datatype matrix multiplication within the BLIS framework

Field G. Van Zee, Devangi N. Parikh, Robert A. van de Geijn

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Tags: Computer science, Matrix multiplication, OpenMP, Package

January 27, 2019 by hgpu

Efficient Implementation and Optimization of Geometric Multigrid Operations in the LIFT Framework

Martin Lucke

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Tags: Computer science, Differential equations, nVidia, nVidia GeForce GTX 1080, OpenCL, Partial differential equations, PDEs, performance portability, Thesis

January 27, 2019 by hgpu

AccUDNN: A GPU Memory Efficient Accelerator for Training Ultra-deep Deep Neural Networks

Jinrong Guo, Wantao Liu, Wang Wang, Qu Lu, Songlin Hu, Jizhong Han, Ruixuan Li

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Tags: Computer science, CUDA, Deep learning, Neural networks, nVidia, Tesla M40

January 27, 2019 by hgpu

Direct N-body code on low-power embedded ARM GPUs

David Goz, Sara Bertocco, Luca Tornatore, Giuliano Taffoni

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Tags: ARM, Astrophysics, FPGA, Heterogeneous systems, Instrumentation and Methods for Astrophysics, N-body simulation, OpenCL, OpenMPI, SoC

January 27, 2019 by hgpu

Exploring FPGA-specific Optimizations for Irregular OpenCL Applications

Mohamed W. Hassan, Ahmed E. Helal, Peter M. Athanas, Wu-Chun Feng, Yasser Y. Hanafy

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Tags: Benchmarking, Computer science, FPGA, HLS, Linear Algebra, OpenCL, Package

January 20, 2019 by hgpu

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

Analyzing the Performance Portability of SYCL across CPUs, GPUs, and Hybrid Systems with Protein Database Search

tdg-benchs: benchmarks used to test the performance of taskgraph

Leveraging the potential of task-based programming with OpenMP task graphs

LLOR: Automatic Repair of OpenMP Programs

LLOR: Automated Repair of OpenMP Programs

Solomon: Simple Off-LOading Macros Orchestrating multiple Notations

Unified schemes for directive-based GPU offloading

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

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high performance computing on graphics processing units: hgpu.org

Applications

Hierarchical Matrix Operations on GPUs: Matrix-Vector Multiplication and Compression

ThunderGBM: Fast GBDTs and Random Forests on GPUs

Swizzle Inventor: Data Movement Synthesis for GPU Kernels

The OoO VLIW JIT Compiler for GPU Inference

High Performance Algorithms for Counting Collisions and Pairwise Interactions

DeepSZ: A Novel Framework to Compress Deep Neural Networks by Using Error-Bounded Lossy Compression

Exploiting OpenMP & OpenACC to Accelerate a Molecular Docking Mini-App in Heterogeneous HPC Nodes

Supporting mixed-datatype matrix multiplication within the BLIS framework

Efficient Implementation and Optimization of Geometric Multigrid Operations in the LIFT Framework

AccUDNN: A GPU Memory Efficient Accelerator for Training Ultra-deep Deep Neural Networks

Direct N-body code on low-power embedded ARM GPUs

Exploring FPGA-specific Optimizations for Irregular OpenCL Applications

Recent source codes

Matrix multiplication using Tensor Cores in CUDA

CPP Joules: Energy Measurement tool for CPP/CUDA programs

HPC-Coder-v2

Reproducible Study and Performance Analysis of GPU Programming Paradigms: OpenACC vs. CUDA in Key Linear Algebra Computations

SW#SYCL

tdg-benchs: benchmarks used to test the performance of taskgraph

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

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