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Deep Learning for Computational Chemistry

Garrett B. Goh, Nathan O. Hodas, Abhinav Vishnu

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Tags: Algorithms, Chemistry, Computational chemistry, Computer science, Deep learning, Machine learning, Neural networks, Review

January 19, 2017 by hgpu

Comparing Parallel Hardware Architectures for Visually Guided Robot Navigation

Wolfram Schenck, Michael Horst, Tim Tiedemann, Sergius Gaulik, Ralf Moller

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Tags: ATI, ATI Radeon HD 7970, Computer science, Computer vision, FPGA, nVidia, nVidia GeForce GTX 570, nVidia Quadro NVS 4200 M, OpenCL, Review, Robotics

July 11, 2016 by hgpu

Parallel Programming Models for Dense Linear Algebra on Heterogeneous Systems

M. Abalenkovs, A. Abdelfattah, J. Dongarra, M. Gates, A. Haidar, J. Kurzak, P. Luszczek, S. Tomov, I. Yamazaki, A. YarKhan

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Tags: Computer science, CUDA, Heterogeneous systems, Linear Algebra, nVidia, OpenCL, Programming techniques, Review, Tesla K40

April 19, 2016 by hgpu

Deep learning review and its applications

Andoni Azkarate Saiz

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Tags: Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 660, Review, Thesis

February 1, 2016 by hgpu

A Survey Of Techniques for Architecting and Managing Asymmetric Multicore Processors

Sparsh Mittal

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Tags: asymmetric multicore processor (AMP), big/little system, classification, heterogeneous multicore architecture, reconfigurable AMP, Review, survey

November 13, 2015 by sparsh0mittal

Sequential Code Parallelization for Multi-core Embedded Systems: A Survey of Models, Algorithms and Tools

Jorge Alberto Castro Godinez

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Tags: Computer science, Parallelization, Review, Thesis

October 22, 2015 by hgpu

Use of modern GPUs in Design Optimization

M.H. Aissa, T. Verstraete, C. Vuik

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Tags: Computer science, Optimization, Review

May 19, 2015 by hgpu

A Survey Of Architectural Approaches for Data Compression in Cache and Main Memory Systems

Sparsh Mittal and Jeffrey S. Vetter

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Tags: 3D memory, bandwidth compression, cache, classification, cpu, GPU, HPC, main memory, NVM, Review

May 18, 2015 by sparsh0mittal

Pseudorandom Numbers Generation for Monte Carlo Simulations on GPUs: OpenCL Approach

Vadim Demchik

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Source codes

Tags: ATI, ATI Radeon HD 5870, ATI Radeon HD 6970, Computer science, Monte Carlo simulation, nVidia, nVidia GeForce GTX 560, nVidia GeForce GTX 560 M, nVidia GeForce GTX 780, OpenCL, Package, Pseudo-random number generators, Review, Tesla K40

March 25, 2015 by hgpu

A Review of CUDA, MapReduce, and Pthreads Parallel Computing Models

Kato Mivule, Benjamin Harvey, Crystal Cobb, Hoda El Sayed

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Tags: Computer science, CUDA, MapReduce, nVidia, Overview, Pthreads, Review, Tesla K20

October 18, 2014 by hgpu

Interactive Wave Simulations

Akash Mittal

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Tags: CUDA, Fluid dynamics, Fluid simulation, nVidia, Review, Thesis, Visualization

September 15, 2014 by hgpu

Improvements to Physically Based Cloth Simulation

Tsz Ho Wong

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Tags: 3D Graphics and Realism, Collision detection, Computer science, CUDA, nVidia, nVidia GeForce GTX 470, nVidia GeForce GTX 780, Review, Thesis

September 9, 2014 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

Deep Learning for Computational Chemistry

Comparing Parallel Hardware Architectures for Visually Guided Robot Navigation

Parallel Programming Models for Dense Linear Algebra on Heterogeneous Systems

Deep learning review and its applications

A Survey Of Techniques for Architecting and Managing Asymmetric Multicore Processors

Sequential Code Parallelization for Multi-core Embedded Systems: A Survey of Models, Algorithms and Tools

Use of modern GPUs in Design Optimization

A Survey Of Architectural Approaches for Data Compression in Cache and Main Memory Systems

Pseudorandom Numbers Generation for Monte Carlo Simulations on GPUs: OpenCL Approach

A Review of CUDA, MapReduce, and Pthreads Parallel Computing Models

Interactive Wave Simulations

Improvements to Physically Based Cloth Simulation

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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