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Efficient Static and Dynamic Memory Management Techniques for Multi-GPU Systems

Max Grossman, Mauricio Araya-Polo

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Tesla K10

December 1, 2015 by hgpu

Bridging OpenCL and CUDA: A Comparative Analysis and Translation

Junghyun Kim, Thanh Tuan Dao, Jaehoon Jung, Jinyoung Joo, Jaejin Lee

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Tags: ATI, ATI Radeon HD 7970, Compilers, Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX Titan, OpenCL

December 1, 2015 by hgpu

Orchestrating Multiple Data-Parallel Kernels on Multiple Devices

Janghaeng Lee, Mehrzad Samadi, Scott Mahlke

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Tags: Computer science, Heterogeneous systems, nVidia, nVidia GeForce GTX 750, nVidia GeForce GTX 760, OpenCL

November 29, 2015 by hgpu

Acceleration of Agent-Based Pandemic Modeling on Multiple GPUs

Barzan Shekh

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Tesla K20, Thesis

November 25, 2015 by hgpu

Optimization of a Machine Learning Algorithm on the Heterogeneous system using OpenCL

Min Gyung Song, Dongweon Yoon

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Tags: Algorithms, AMD Radeon R9 290, ATI, Clustering, Computer science, Heterogeneous systems, Machine learning, OpenCL

November 25, 2015 by hgpu

TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

Martin Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Jozefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dan Mane, Rajat Monga, Sherry Moore, Derek Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda Viegas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, Xiaoqiang Zheng

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Tags: Computer science, Computer vision, CUDA, Deep learning, Heterogeneous systems, Information Retrieval, Machine learning, Neural networks, nVidia, Package, Speech recognition

November 11, 2015 by hgpu

Climbing Mont Blanc – A Training Site for Energy Efficient Programming on Heterogeneous Multicore Processors

Lasse Natvig, Torbjorn Follan, Simen Stoa, Sindre Magnussen, Antonio Garcia Guirado

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Tags: Computer science, Energy-efficient computing, Heterogeneous systems, OpenCL, OpenMP, Pthreads

November 11, 2015 by hgpu

High Performance Adaptive Image Processing on Multi-scale Hybrid Architectures

Fangbin Liu

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Tags: Algorithms, CUDA, Distributed computing, Heterogeneous systems, Image processing, Matrix multiplication, nVidia, nVidia GeForce GTX 295, Thesis

November 10, 2015 by hgpu

On the Effectiveness of OpenMP teams for Programming Embedded Manycore Accelerators

Alessandro Capotondi, Andrea Marongiu

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Tags: Computer science, Heterogeneous systems, OpenMP, Performance, SoC

November 8, 2015 by hgpu

Heterogeneous CPU/(GP) GPU Memory Hierarchy Analysis and Optimization

Josue Vladimir Quiroga Esparza

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Tags: Computer science, CUDA, Heterogeneous systems, Memory, nVidia, Thesis

November 4, 2015 by hgpu

Energy-Efficient Execution of Data-Parallel Applications on Heterogeneous Mobile Platforms

Alok Prakash, Siqi Wang, Alexandru Eugen Irimiea, Tulika Mitra

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Tags: ARM, Computer science, Heterogeneous systems, OpenCL, SoC

October 31, 2015 by hgpu

Execution of Compound Multi-Kernel OpenCL Computations in Multi-CPU/Multi-GPU Environments

Fabio Soldado, Fernando Alexandre, Herve Paulino

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Tags: ATI, ATI Radeon HD 7950, Computer science, Heterogeneous systems, OpenCL, Performance

October 25, 2015 by hgpu

CuPBoP-AMD: Extending CUDA to AMD Platforms

CuPBoP: Making CUDA a Portable Language

Adopter: Automated Deep Learning Optimization via DSL-based Source Code Transformation

Automated Deep Learning Optimization via DSL-Based Source Code Transformation

ROCm's implementation of Gromacs

GROMACS on AMD GPU-Based HPC Platforms: Using SYCL for Performance and Portability

Code examples for paper on SYCL backend of Kokkos - IWOCL 2024

Experiences with implementing Kokkos’ SYCL backend

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

GPU plugin for PySCF

Python-Based Quantum Chemistry Calculations with GPU Acceleration

QArray

QArray: a GPU-accelerated constant capacitance model simulator for large quantum dot arrays

Celerity: High-level C++ for Accelerator Clusters

Balancing Tracking Granularity and Parallelism in Many-Task Systems: The Horizons Approach

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

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