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

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

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

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

Optical flow algorithms for SYCL

SYCL in the edge: performance and energy evaluation for heterogeneous acceleration

OpenMP5-Offload-OpenMC-Intel-PVC

Distributed OpenMP Offloading of OpenMC on Intel GPU MAX Accelerators

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

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

Exploiting Task Parallelism with OpenCL: A Case Study

Recent source codes

QArray

Celerity: High-level C++ for Accelerator Clusters

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

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

Optical flow algorithms for SYCL

OpenMP5-Offload-OpenMC-Intel-PVC

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