high performance computing on graphics processing units: hgpu.org

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

HLS Portability from Intel to Xilinx: A Case Study

HEXL: Intel Homomorphic Encryption Acceleration Library

Accelerating Encrypted Computing on Intel GPUs

Taskflow: A General-purpose Parallel and Heterogeneous Task Programming System

Taskflow: A Lightweight Parallel and Heterogeneous Task Graph Computing System

CompilerGym: a library performant reinforcement learning environments for compiler tasks

CompilerGym: Robust, Performant Compiler Optimization Environments for AI Research

HPCToolkit

Measurement and Analysis of GPU-accelerated Applications with HPCToolkit

NVPTX-SPIR-V Translator

Supporting CUDA for an extended RISC-V GPU architecture

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high performance computing on graphics processing units: hgpu.org

TENSILE: A Tensor granularity dynamic GPU memory scheduler method towards multiple dynamic workloads system

Energy-aware Task Scheduling with Deadline Constraint in DVFS-enabled Heterogeneous Clusters

Nimble: Lightweight and Parallel GPU Task Scheduling for Deep Learning

Towards Co-execution on Commodity Heterogeneous Systems: Optimizations for Time-Constrained Scenarios

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

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