high performance computing on graphics processing units: hgpu.org

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Let’s sort this out: GPGPU Verification of Radix Sort

Dré van Oorschot

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Tags: Algorithms, Computer science, Package, Sorting

February 23, 2020 by hgpu

EASYPAP: a Framework for Learning Parallel Programming

Alice Lasserre, Raymond Namyst, Pierre-André Wacrenier

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Tags: Algorithms, AVX, Computer science, Education, MPI, OpenCL, OpenMP, Package, Pthreads

February 16, 2020 by hgpu

Task-based, GPU-accelerated and Robust Library for Solving Dense Nonsymmetric Eigenvalue Problems

Mirko Myllykoski, Carl Christian Kjelgaard Mikkelsen

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Tags: Computer science, CUDA, Mathematical Software, nVidia, Package, Tesla V100

February 16, 2020 by hgpu

Working With Incremental Spatial Data During Parallel (GPU) Computation

Robert Chisholm

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Tags: Agent-based modeling, Computer science, CUDA, nVidia, nVidia GeForce GTX Titan V, Package, Thesis

February 9, 2020 by hgpu

Automated Runtime Analysis and Adaptation for Scalable Heterogeneous Computing

Ahmed E. Helal

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Tags: Computer science, CUDA, HPC, nVidia, OpenCL, OpenMP, Package, Performance, Tesla M2050, Thesis

February 9, 2020 by hgpu

A Language for Describing Optimization Strategies

Bastian Hagedorn, Johannes Lenfers, Thomas Koehler, Sergei Gorlatch, Michel Steuwer

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Tags: Computer science, DSL, High-level Languages, OpenCL, Package, Scala

February 9, 2020 by hgpu

Non-Determinism in TensorFlow ResNets

Miguel Morin, Matthew Willetts

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Tags: Computer science, Deep learning, Machine learning, nVidia, Package, TensorFlow, Tesla M60

February 2, 2020 by hgpu

Interoperable GPU Kernels as Latency Improver for MEC

Juuso Haavisto, Jukka Riekki

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Tags: Computer science, GLSL, Graphics, nVidia, nVidia GeForce RTX 2080, nVidia Jetson TX2, Package, Vulkan

February 2, 2020 by hgpu

An Image Enhancing Pattern-based Sparsity for Real-time Inference on Mobile Devices

Xiaolong Ma, Wei Niu, Tianyun Zhang, Sijia Liu, Fu-Ming Guo, Sheng Lin, Hongjia Li, Xiang Chen, Jian Tang, Kaisheng Ma, Bin Ren, Yanzhi Wang

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Tags: ARM, Computer science, Computer vision, CUDA, Deep learning, Machine learning, nVidia, nVidia GeForce RTX 2080 Ti, OpenCL, Package

January 26, 2020 by hgpu

md_poly: A Performance-Portable Polyhedral Compiler Based on Multi-Dimensional Homomorphisms

Ari Rasch, Richard Schulze, Sergei Gorlatch

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Tags: Code generation, Compilers, Computer science, nVidia, OpenCL, Package, performance portability, Tesla V100

January 19, 2020 by hgpu

On Demand Solid Texture Synthesis Using Deep 3D Networks

Jorge Gutierrez, Julien Rabin, Bruno Galerne, Thomas Hurtut

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Tags: 3D Graphics and Realism, Deep learning, nVidia, nVidia GeForce GTX 1080 Ti, nVidia GeForce RTX 2080 Ti, OpenGL, Package, PyTorch

January 19, 2020 by hgpu

Towards High Performance Java-based Deep Learning Frameworks

Athanasios Stratikopoulos, Juan Fumero, Zoran Sevarac, Christos Kotselidis

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Tags: Computer science, Computer vision, CUDA, Data mining, Deep learning, Heterogeneous systems, Java, Machine learning, nVidia, OpenCL, Package

January 19, 2020 by hgpu

hpcbench: A set of benchmarking utilities for biomolecular simulation tools

Engineering Supercomputing Platforms for Biomolecular Applications

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

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high performance computing on graphics processing units: hgpu.org

Packages

Let’s sort this out: GPGPU Verification of Radix Sort

EASYPAP: a Framework for Learning Parallel Programming

Task-based, GPU-accelerated and Robust Library for Solving Dense Nonsymmetric Eigenvalue Problems

Working With Incremental Spatial Data During Parallel (GPU) Computation

Automated Runtime Analysis and Adaptation for Scalable Heterogeneous Computing

A Language for Describing Optimization Strategies

Non-Determinism in TensorFlow ResNets

Interoperable GPU Kernels as Latency Improver for MEC

An Image Enhancing Pattern-based Sparsity for Real-time Inference on Mobile Devices

md_poly: A Performance-Portable Polyhedral Compiler Based on Multi-Dimensional Homomorphisms

On Demand Solid Texture Synthesis Using Deep 3D Networks

Towards High Performance Java-based Deep Learning Frameworks

Recent source codes

hpcbench: A set of benchmarking utilities for biomolecular simulation tools

HPCTransCompile: An AI Compiler Generated Dataset for High-Performance CUDA Transpilation and LLM Preliminary Exploration

chemtrain: Training Molecular Dynamics Potentials in JAX

microSYCL: SYCL micro-benchmarks repository

XaaS containers

CASS: Cuda-Amd aSSembly

Cluser of smartphones for edge computing application using TensorFlow

SYCL Container

Efficient Graph Embedding at Scale: Optimizing CPU-GPU-SSD Integration

Can Large Language Models Predict Parallel Code Performance?

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