high performance computing on graphics processing units: hgpu.org

Applications

hgpu.org » Applications

Revisiting Online Autotuning for Sparse-Matrix Vector Multiplication Kernels on High-Performance Accelerators

Simon Garcia De Gonzalo, Wen-Mei Hwu, Simon D. Hammond, Christian R. Trott

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Tags: Computer science, Intel Xeon Phi, nVidia, Performance, Sparse matrix, Tesla P100

July 15, 2018 by hgpu

Multicore architecture and cache optimization techniques for solving graph problems

Alvaro Tzul

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Tags: Computer science, CUDA, Graph theory, nVidia

July 15, 2018 by hgpu

CloudCL: Single-Paradigm Distributed Heterogeneous Computing for Cloud Infrastructures

Max Plauth, Florian Roesler, Andreas Polze

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Tags: Cloud, Computer science, Java, MPI, nVidia, nVidia GRID K520, OpenCL, Package

July 15, 2018 by hgpu

Data-Parallel Hashing Techniques for GPU Architectures

Brenton Lessley

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Tags: Computer science, CUDA, Hashing, nVidia

July 15, 2018 by hgpu

Application of Deep-Learning to Compiler-Based Graphs

Tristan Vanderbruggen

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Tags: Compilers, Computer science, Deep learning, Graph theory, Machine learning, Neural networks, nVidia, nVidia GRID K520, OpenCL, Thesis

July 7, 2018 by hgpu

Energy Consumption of Algorithms for Solving the Compressible Navier-Stokes Equations on CPU’s, GPU’s and KNL’s

Satya P. Jammy, Christian T. Jacobs, David J. Lusher, Neil D. Sandham

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Tags: CUDA, Finite difference, Fluid dynamics, Intel Xeon Phi, Navier-Stokes equations, NSEs, nVidia, Tesla K40

July 7, 2018 by hgpu

Calamari – A High-Performance Tensorflow-based Deep Learning Package for Optical Character Recognition

Christoph Wick, Christian Reul, Frank Puppe

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Tags: Computer science, Deep learning, Neural networks, nVidia, nVidia GeForce GTX 1080 Ti, Package, Python, TensorFlow

July 7, 2018 by hgpu

FluidFFT: common API (C++ and Python) for Fast Fourier Transform HPC libraries

Ashwin Vishnu Mohanan, Cyrille Bonamy, Pierre Augier

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Tags: Benchmarking, cfd, CUDA, FFT, Fluid dynamics, MPI, Package, Python

July 7, 2018 by hgpu

An Efficient Dispatcher for Large Scale GraphProcessing on OpenCL-based FPGAs

Chengbo Yang

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Tags: Computer science, FPGA, Graph theory, OpenCL, Task scheduling

July 7, 2018 by hgpu

Beyond Straightforward Vectorization of Lightweight Data Compression Algorithms for Larger Vector Sizes

Johannes Pietrzyk, Annett Ungethum, Dirk Habich, Wolfgang Lehner

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Tags: Algorithms, Compression, Computer science, Intel Xeon Phi

July 5, 2018 by hgpu

Exploration of Low Numeric Precision Deep Learning Inference Using Intel FPGAs

Philip Colangelo, Nasibeh Nasiri, Asit Mishra, Eriko Nurvitadhi, Martin Margala, Kevin Nealis

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Tags: CNN, Computer science, Deep learning, FPGA, OpenCL

July 5, 2018 by hgpu

Evaluating the Efficiency of CPUs, GPUs and FPGAs on a Near-Duplicate Document Detection Via OpenCL

Ercan Canhasi

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Tags: Computer science, FPGA, Machine learning, NLP, OpenCL

July 5, 2018 by hgpu

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

Polygeist: C/C++ frontend for MLIR

Retargeting and Respecializing GPU Workloads for Performance Portability

Parallel Gaussian process with kernel approximation in CUDA

See all packages

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high performance computing on graphics processing units: hgpu.org

Applications

Revisiting Online Autotuning for Sparse-Matrix Vector Multiplication Kernels on High-Performance Accelerators

Multicore architecture and cache optimization techniques for solving graph problems

Data-Parallel Hashing Techniques for GPU Architectures

Application of Deep-Learning to Compiler-Based Graphs

Energy Consumption of Algorithms for Solving the Compressible Navier-Stokes Equations on CPU’s, GPU’s and KNL’s

Calamari – A High-Performance Tensorflow-based Deep Learning Package for Optical Character Recognition

FluidFFT: common API (C++ and Python) for Fast Fourier Transform HPC libraries

An Efficient Dispatcher for Large Scale GraphProcessing on OpenCL-based FPGAs

Beyond Straightforward Vectorization of Lightweight Data Compression Algorithms for Larger Vector Sizes

Exploration of Low Numeric Precision Deep Learning Inference Using Intel FPGAs

Evaluating the Efficiency of CPUs, GPUs and FPGAs on a Near-Duplicate Document Detection Via OpenCL

Recent source codes

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

Polygeist: C/C++ frontend for MLIR

Parallel Gaussian process with kernel approximation in CUDA

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