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MPC: A Massively Parallel Compression Algorithm for Scientific Data

Annie Yang, Hari Mukka, Farbod Hesaaraki, Martin Burtscher

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Tags: Algorithms, Compression, Computer science, CUDA, nVidia, Tesla K40

August 14, 2015 by hgpu

Bufferless NOC Simulation of Large Multicore System on GPU Hardware

Navin Kumar, Aryabartta Sahu

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Tags: Computer science, CUDA, nVidia, nVidia GeForce GTX 690

August 14, 2015 by hgpu

Automatic classification of object code using machine learning

John Clemens

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Tags: Computer science, CUDA, Machine learning, nVidia, Security

August 14, 2015 by hgpu

Processing Markov Logic Networks with GPUs

Carlos Alberto Martinez-Angeles, Ines Dutra, Vitor Santos Costa, Jorge Buenabad-Chavez

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Tags: Computer science, CUDA, Databases, Machine learning, nVidia, Tesla K40

August 14, 2015 by hgpu

An Introduction to High Performance Computing on AWS

David Pellerin, Dougal Ballantyne, Adam Boeglin

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Tags: Cloud, Cluster computing, Computer science, CUDA, OpenCL

August 13, 2015 by hgpu

Perception of Acoustical Spatial Attributes and Impression in Virtually Rendered Sound Field

Yukio Iwaya, Makoto Otani, Takao Tsuchiya, Yasushi Inoguchi

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Tags: Acoustics, Computer science, CUDA, GPU cluster, nVidia, OpenMPI, Tesla M2075

August 13, 2015 by hgpu

Trainable Nonlinear Reaction Diffusion: A Flexible Framework for Fast and Effective Image Restoration

Yunjin Chen, Thomas Pock

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Tags: Computer vision, CUDA, Image processing, nVidia, nVidia GeForce GTX 780 Ti, Package, Signal denoising

August 13, 2015 by hgpu

Acceleration-as-a-Service: Exploiting Virtualised GPUs for a Financial Application

Blesson Varghese, Javier Prades, Carlos Reano, Federico Silla

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Tags: Computer science, CUDA, Finance, nVidia, Tesla K20, Virtualization

August 12, 2015 by hgpu

Accelerating IISPH: A Parallel GPGPU Solution Using CUDA

Andre Eliasson, Pontus Franzen

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Tags: Algorithms, CUDA, Fluid dynamics, Fluid simulation, nVidia, nVidia GeForce GTX 970, nVidia Quadro K4000, OpenMP, Thesis

August 12, 2015 by hgpu

GPU Pro 6: Advanced Rendering Techniques

Wolfgang Engel (editor)

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Tags: 3D Graphics and Realism, Book, Computer science, CUDA, DirectCompute, DirectX, Games, nVidia, OpenCL, OpenGL, Rendering, Visualization

August 12, 2015 by hgpu

Performance analysis of parallel gravitational N-body codes on large GPU cluster

Siyi Huang, Rainer Spurzem, Peter Berczik

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Tags: Astrophysics, CUDA, GPU cluster, Gravitation, Instrumentation and Methods for Astrophysics, N-body simulation, nVidia, Performance, Tesla M2050, Tesla M2070

August 12, 2015 by hgpu

Efficient Numerical Evaluation of Feynman Integral

Zhao Li, Jian Wang, Qi-Shu Yan, Xiaoran Zhao

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Tags: CUDA, High Energy Physics - Phenomenology, nVidia, Physics, QCD, Tesla K20

August 12, 2015 by hgpu

CFAL-bench

Comparing Parallel Functional Array Languages: Programming and Performance

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

Can Large Language Models Predict Parallel Code Performance?

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

DeepCompile: A Compiler-Driven Approach to Optimizing Distributed Deep Learning Training

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

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high performance computing on graphics processing units: hgpu.org

MPC: A Massively Parallel Compression Algorithm for Scientific Data

Bufferless NOC Simulation of Large Multicore System on GPU Hardware

Automatic classification of object code using machine learning

Processing Markov Logic Networks with GPUs

Perception of Acoustical Spatial Attributes and Impression in Virtually Rendered Sound Field

Trainable Nonlinear Reaction Diffusion: A Flexible Framework for Fast and Effective Image Restoration

Acceleration-as-a-Service: Exploiting Virtualised GPUs for a Financial Application

Accelerating IISPH: A Parallel GPGPU Solution Using CUDA

GPU Pro 6: Advanced Rendering Techniques

Performance analysis of parallel gravitational N-body codes on large GPU cluster

Efficient Numerical Evaluation of Feynman Integral

Recent source codes

CFAL-bench

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

Can Large Language Models Predict Parallel Code Performance?

PELSI: Power-Efficient Layer-Switched Inference

Ouroboros: Virtualized Queues for dynamic memory management

MSCCL++: A GPU-driven communication stack for scalable AI applications

Benchmark compute shader of Unity against InteropUnityCUDA

Data-efficient LLM Fine-tuning for Code Generation

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

Large Language Model Powered C-to-CUDA Code Translation: A Novel Auto-Parallelization Framework

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