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Co-tuning of Software Specializers and Hardware Accelerators within a CNN Application

Sean Roberts

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Tags: ARM, CNN, Computer science, Deep learning, FPGA, Neural networks, SoC

June 7, 2016 by hgpu

DeepX: A Software Accelerator for Low-Power Deep Learning Inference on Mobile Devices

Nicholas D. Lane, Sourav Bhattacharya, Petko Georgiev, Claudio Forlivesi, Lei Jiao, Lorena Qendro, Fahim Kawsar

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Tags: Computer science, CUDA, Deep learning, Heterogeneous systems, nVidia, nVidia Jetson TK1, SoC

March 15, 2016 by hgpu

Heterogeneous parallel algorithms for Computational Fluid Dynamics on unstructured meshes

Guillermo Andres Oyarzun Altamirano

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Tags: cfd, CUDA, Fluid dynamics, MPI, nVidia, OpenCL, SoC, Tesla M2090, Thesis

March 5, 2016 by hgpu

GPGPU Multi Object Bayesian Tracking with an embedded System on a Chip

David Webb

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Tags: Bayesian, Computer science, Computer vision, CUDA, FPGA, Heterogeneous systems, nVidia, nVidia GeForce GTX 960, nVidia Jetson TK1, SoC, Thesis

February 2, 2016 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

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

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

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high performance computing on graphics processing units: hgpu.org

Co-tuning of Software Specializers and Hardware Accelerators within a CNN Application

DeepX: A Software Accelerator for Low-Power Deep Learning Inference on Mobile Devices

Heterogeneous parallel algorithms for Computational Fluid Dynamics on unstructured meshes

GPGPU Multi Object Bayesian Tracking with an embedded System on a Chip

On the Effectiveness of OpenMP teams for Programming Embedded Manycore Accelerators

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

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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