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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

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

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

A Survey on Agent-based Simulation using Hardware Accelerators

Jiajian Xiao, Philipp Andelfinger, David Eckhoff, Wentong Cai, Alois Knoll

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Tags: Computer science, CUDA, FPGA, Heterogeneous systems, nVidia, OpenCL, Overview

July 5, 2018 by hgpu

XGBoost: Scalable GPU Accelerated Learning

Rory Mitchell, Andrey Adinets, Thejaswi Rao, Eibe Frank

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Tags: Computer science, CUDA, Java, Machine learning, nVidia, Package, Python, R, Scala, Tesla V100

July 5, 2018 by hgpu

Directive-Based, High-Level Programming and Optimizations for High-Performance Computing with FPGAs

Jacob Lambert, Seyong Lee, Jungwon Kim, Jeffrey S. Vetter, Allen D. Malony

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Tags: Computer science, FPGA, nVidia, OpenACC, OpenCL, Tesla K40

July 1, 2018 by hgpu

Analysis-driven Engineering of Comparison-based Sorting Algorithms on GPUs

Ben Karsin, Volker Weichert, Henri Casanova, John Iacono, Nodari Sitchinava

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 770, nVidia Quadro M 4000, Performance, Sorting, Tesla K40

July 1, 2018 by hgpu

Specx: Speculative task-based runtime system

Specx: a C++ task-based runtime system for heterogeneous distributed architectures

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation

KISim: Kubernetes Intelligent Scheduling Simulator

KIS-S: A GPU-Aware Kubernetes Inference Simulator with RL-Based Auto-Scaling

Hardware Compute Partitioning on NVIDIA GPUs for Composable Systems

Efficient GPU Implementation of Multi-Precision Integer Division

ParEval: A Parallel Code Evaluation Benchmark

ParEval-Repo: A Benchmark Suite for Evaluating LLMs with Repository-level HPC Translation Tasks

FlashSparse: Minimizing Computation Redundancy for Fast Sparse Matrix Multiplications on Tensor Cores

Libra: Synergizing CUDA and Tensor Cores for High-Performance Sparse Matrix Multiplication

exa-AMD: Exascale Accelerated Materials Discovery

Accelerated discovery and design of Fe-Co-Zr magnets with tunable magnetic anisotropy through machine learning and parallel computing

WiLLM: An Open Wireless LLM Communication System

Vcc: the Vulkan Clang Compiler

No More Shading Languages: Compiling C++ to Vulkan Shaders

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high performance computing on graphics processing units: hgpu.org

Data-Parallel Hashing Techniques for GPU Architectures

Application of Deep-Learning to Compiler-Based Graphs

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

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

A Survey on Agent-based Simulation using Hardware Accelerators

XGBoost: Scalable GPU Accelerated Learning

Directive-Based, High-Level Programming and Optimizations for High-Performance Computing with FPGAs

Analysis-driven Engineering of Comparison-based Sorting Algorithms on GPUs

Recent source codes

Specx: Speculative task-based runtime system

Mutual-Supervised Learning for Sequential-to-Parallel Code Translation

KISim: Kubernetes Intelligent Scheduling Simulator

Hardware Compute Partitioning on NVIDIA GPUs for Composable Systems

Efficient GPU Implementation of Multi-Precision Integer Division

ParEval: A Parallel Code Evaluation Benchmark

FlashSparse: Minimizing Computation Redundancy for Fast Sparse Matrix Multiplications on Tensor Cores

exa-AMD: Exascale Accelerated Materials Discovery

WiLLM: An Open Wireless LLM Communication System

Vcc: the Vulkan Clang Compiler

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