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Exploring Portability and Performance of OpenCL FPGA Kernels on Intel HARPv2

Anthony M. Cabrera, Roger D. Chamberlain

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Tags: Computer science, FPGA, Heterogeneous systems, HLS, OpenCL

July 7, 2019 by hgpu

FusionAccel: A General Re-configurable Deep Learning Inference Accelerator on FPGA for Convolutional Neural Networks

Shi Shi

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Tags: Computer science, Deep learning, FPGA, Hardware Architecture, Neural networks

July 7, 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

LAMDA: Learning-Assisted Multi-Stage Autotuning for FPGA Design Closure

Ecenur Ustun, Shaojie Xiang, Jinny Gui, Cunxi Yu, Zhiru Zhang

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Tags: Computer science, FPGA, OpenCL, Performance

June 9, 2019 by hgpu

The Accelerator Wall: Limits of Chip Specialization

Adi Fuchs, David Wentzlaff

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Tags: ASIC, Computer science, FPGA

June 2, 2019 by hgpu

Heterogeneous Resource-Elastic Scheduling for CPU+FPGA Architectures

Anuj Vaishnav, Khoa Dang Pham, Dirk Koch

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Tags: Computer science, FPGA, Heterogeneous systems, OpenCL

June 2, 2019 by hgpu

Acceleration of Scientific Deep Learning Models on Heterogeneous Computing Platform with Intel FPGAs

C. Jiang, D. Ojika, T. Kurth, Prabhat, S. Vallecorsa, B. Patel, H. Lam

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Tags: Computer science, Deep learning, FPGA, Heterogeneous systems, Neural networks

May 26, 2019 by hgpu

Comparing Energy Efficiency of CPU, GPU and FPGA Implementations for Vision Kernels

Murad Qasaimeh, Kristof Denolf, Jack Lo, Kees Vissers, Joseph Zambreno, Phillip H. Jones

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Tags: ARM, Benchmarking, Computer science, Computer vision, CUDA, FPGA, nVidia, nVidia Jetson TX2, OpenCV, Package

May 26, 2019 by hgpu

Accelerating Deterministic and Stochastic Binarized Neural Networks on FPGAs Using OpenCL

Corey Lammie, Wei Xiang, Mostafa Rahimi Azghadi

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Tags: Computer science, Deep learning, FPGA, Heterogeneous systems, Neural networks, OpenCL

May 19, 2019 by hgpu

OpenDNN: An Open-source, cuDNN-like Deep Learning Primitive Library

Daeyeon Kim

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Tags: Computer science, Deep learning, FPGA, Neural networks, OpenCL, Performance, Thesis

May 19, 2019 by hgpu

FPGA Implementation of Reduced Precision Convolutional Neural Networks

Muhammad Mohid Nabil

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Tags: Computer science, CUDA, Deep learning, FPGA, HLS, Image recognition, Machine learning, Neural networks, nVidia, nVidia GeForce GTX 1080, Precision, Thesis

May 12, 2019 by hgpu

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

Profile Util library: A quick and easy way to get MPI, OpenMP and GPU runtime information

MaC: Mamba CPU performance predictor

MambaCPU: Enhanced Correlation Mining with State Space Models for CPU Performance Prediction

Mixed-precision finite element kernels

Mixed-precision finite element kernels and assembly: Rounding error analysis and hardware acceleration

SHMT: The Simultaneous and Heterogenous Multithreading project

General-Purpose Computing on Tensor Processors

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

Online Energy Optimization in GPUs: A Multi-Armed Bandit Approach

See all packages

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high performance computing on graphics processing units: hgpu.org

Exploring Portability and Performance of OpenCL FPGA Kernels on Intel HARPv2

FusionAccel: A General Re-configurable Deep Learning Inference Accelerator on FPGA for Convolutional Neural Networks

LAMDA: Learning-Assisted Multi-Stage Autotuning for FPGA Design Closure

The Accelerator Wall: Limits of Chip Specialization

Heterogeneous Resource-Elastic Scheduling for CPU+FPGA Architectures

Acceleration of Scientific Deep Learning Models on Heterogeneous Computing Platform with Intel FPGAs

Comparing Energy Efficiency of CPU, GPU and FPGA Implementations for Vision Kernels

Accelerating Deterministic and Stochastic Binarized Neural Networks on FPGAs Using OpenCL

OpenDNN: An Open-source, cuDNN-like Deep Learning Primitive Library

FPGA Implementation of Reduced Precision Convolutional Neural Networks

Recent source codes

Kokkidio: Kokkos+Eigen - write fast, readable multi-platform code

LLaMA-Inference-Bench

MATAR

Over-synchronization in GPU Programs

profile_util: simple C++ library to report memory, timing, thread affinity

MaC: Mamba CPU performance predictor

Mixed-precision finite element kernels

SHMT: The Simultaneous and Heterogenous Multithreading project

Superpipeline: A Universal Approach for Reducing GPU Memory Usage in Large Models

EnergyUCB-Bandit

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