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Heterogeneity-Aware Cluster Scheduling Policies for Deep Learning Workloads

Deepak Narayanan, Keshav Santhanam, Fiodar Kazhamiaka, Amar Phanishayee, Matei Zaharia

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Tags: Computer science, CUDA, Deep learning, FPGA, GPU cluster, Heterogeneous systems, nVidia, Optimization, Task scheduling, Tesla K80, Tesla P100, Tesla V100

August 30, 2020 by hgpu

PDAWL: Profile-based Iterative Dynamic Adaptive WorkLoad Balance on Heterogeneous Architectures

Tongsheng Geng, Marcos Amaris, Stephane Zuckerman, Alfredo Goldman, Guang R. Gao, Jean-Luc Gaudiot

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Tags: Computer science, CUDA, Heterogeneous systems, Machine learning, nVidia, nVidia GeForce GTX Titan, Performance, Sparse matrix, Task scheduling, Tesla K20, Tesla K40

May 24, 2020 by hgpu

Abstracting OpenCL for Multi-Application Workloads on CPU-FPGA Clusters

Graham Mark Holland

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Tags: ARM, Cloud, Computer science, FPGA, Heterogeneous systems, OpenCL, Task scheduling, Thesis

March 15, 2020 by hgpu

Themis: Fair and Efficient GPU Cluster Scheduling for Machine Learning Workloads

Kshiteej Mahajan, Arjun Singhvi, Arjun Balasubramanian, Varun Batra, Surya Teja Chavali, Shivaram Venkataraman, Aditya Akella, Amar Phanishayee, Shuchi Chawla

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Tags: Computer science, GPU cluster, Machine learning, nVidia, Task scheduling, Tesla K80, Tesla M60

July 4, 2019 by hgpu

HEATS: Heterogeneity- and Energy-Aware Task-based Scheduling

Isabelly Rocha, Christian Göttel, Pascal Felber, Marcelo Pasin, Romain Rouvoy, Valerio Schiavoni

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Tags: ARM, Cloud, Computer science, FPGA, Heterogeneous systems, Package, Task scheduling

June 30, 2019 by hgpu

On Runtime Systems for Task-based Programming on Heterogeneous Platforms

Samuel Thibault

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Tags: Computer science, CUDA, Distributed computing, Heterogeneous systems, nVidia, nVidia Quadro FX 5800, OpenCL, Operating systems, StarPU, Task scheduling, Tesla C2050, Tesla K20, Tesla M2075, Thesis

December 23, 2018 by hgpu

Optimization of a discontinuous finite element solver with OpenCL and StarPU

Philippe Helluy, Laura Mendoza, Bruno Weber

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Tags: Algorithms, Computer science, Hybrid computing, nVidia, nVidia GeForce GTX 1050 Ti, nVidia Quadro P 6000, OpenCL, Package, Task scheduling

December 9, 2018 by hgpu

Exploiting Task Parallelism with OpenCL: A Case Study

Pekka Jaaskelainen, Ville Korhonen, Matias Koskela, Jarmo Takala, Karen Egiazarian, Aram Danielyan, Cristovao Cruz, James Price, Simon McIntosh-Smith

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Tags: Computer science, OpenCL, Package, Task scheduling

October 21, 2018 by hgpu

ZUCL: A ZYNQ UltraScale+ Framework for OpenCL HLS Applications

Khoa Dang Pham, Anuj Vaishnav, Malte Vesper, Dirk Koch

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Tags: Computer science, FPGA, HLS, OpenCL, Package, Task scheduling

September 16, 2018 by hgpu

GPU schedulers: how fair is fair enough?

Tyler Sorensen, Hugues Evrard, Alastair F. Donaldson

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Tags: Computer science, HSA, OpenCL, Task scheduling

August 5, 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

Improving tasks throughput on accelerators using OpenCL command concurrency

A.J. Lazaro-Munoz, J.M. Gonzalez-Linares, J. Gomez-Luna, N. Guil

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Tags: AMD Radeon R9, ATI, Computer science, Heterogeneous systems, Intel Xeon Phi, nVidia, OpenCL, Performance, Task scheduling, Tesla K20

June 28, 2018 by hgpu

FlowPM: Distributed TensorFlow Implementation of the FastPM Cosmological N-body Solver

Hummingbird: a library for compiling trained traditional ML models into tensor computations

A Tensor Compiler for Unified Machine Learning Prediction Serving

Bempp-cl: A fast Python based just-in-time compiling boundary element library

Deep Learning for Digital Asset Limit Order Books

Dream to Control

Mastering Atari with Discrete World Models

visrec-api: specification of standard Visual Recognition API for Java (JSR381)

Transparent Acceleration of Java-based Deep Learning Engines

LoopBench: An Evaluation of Loop Acceleration in Heterogeneous Systems

GemmKernels: Flexible and performant GEMM kernels in Julia

Flexible Performant GEMM Kernels on GPUs

Accelerating Sparse Matrix-Matrix Multiplication with GPU Tensor Cores

Extending High-Level Synthesis for Task-Parallel Programs

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high performance computing on graphics processing units: hgpu.org

Heterogeneity-Aware Cluster Scheduling Policies for Deep Learning Workloads

PDAWL: Profile-based Iterative Dynamic Adaptive WorkLoad Balance on Heterogeneous Architectures

Themis: Fair and Efficient GPU Cluster Scheduling for Machine Learning Workloads

On Runtime Systems for Task-based Programming on Heterogeneous Platforms

Optimization of a discontinuous finite element solver with OpenCL and StarPU

Exploiting Task Parallelism with OpenCL: A Case Study

ZUCL: A ZYNQ UltraScale+ Framework for OpenCL HLS Applications

GPU schedulers: how fair is fair enough?

An Efficient Dispatcher for Large Scale GraphProcessing on OpenCL-based FPGAs

Improving tasks throughput on accelerators using OpenCL command concurrency

Recent source codes

FlowPM: Distributed TensorFlow Implementation of the FastPM Cosmological N-body Solver

Hummingbird: a library for compiling trained traditional ML models into tensor computations

Bempp-cl: A fast Python based just-in-time compiling boundary element library

Deep Learning for Digital Asset Limit Order Books

Dream to Control

visrec-api: specification of standard Visual Recognition API for Java (JSR381)

LoopBench: An Evaluation of Loop Acceleration in Heterogeneous Systems

GemmKernels: Flexible and performant GEMM kernels in Julia

Accelerating Sparse Matrix-Matrix Multiplication with GPU Tensor Cores

Extending High-Level Synthesis for Task-Parallel Programs

Most viewed papers (last 30 days)

Featured events

The 18th International Conference on High Performance Computing & Simulation (HPCS), 2020

The Fifth International Workshop on GPU Computing and AI (GCA), 2020

2nd International Conference on Frontiers of Intelligent Manufacturing and Automation (CFIMA’21), 2021

International Conference on Cyber Physical Systems and IoT (CPSIOT’20), 2020

International Conference on Wireless Networks and Embedded Systems (ICWNES’20), 2020