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Studying the Potential of Automatic Optimizations in the Intel FPGA SDK for OpenCL

Adel Ejjeh, Vikram Adve, Rob Rutenbar

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Tags: Computer science, Design space exploration, FPGA, HLS, OpenCL

January 16, 2022 by hgpu

CFU Playground: Full-Stack Open-Source Framework for Tiny Machine Learning (tinyML) Acceleration on FPGAs

Shvetank Prakash, Tim Callahan, Joseph Bushagour, Colby Banbury, Alan V. Green, Pete Warden, Tim Ansell, Vijay Janapa Reddi

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Tags: Computer science, Design space exploration, FPGA, Machine learning, Package

January 9, 2022 by hgpu

GCN Inference Acceleration using High-Level Synthesis

Yi Chien Lin, Bingyi Zhang, Viktor Prasanna

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Tags: Computer science, Data parallelism, Design space exploration, FPGA, nVidia, nVidia GeForce GTX Titan XP, OpenCL, Package

October 10, 2021 by hgpu

ScaleHLS: Scalable High-Level Synthesis through MLIR

Hanchen Ye, Cong Hao, Jianyi Cheng, Hyunmin Jeong, Jack Huang, Stephen Neuendorffer, Deming Chen

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Tags: Computer science, Design space exploration, FPGA, HLS, Neural networks, Package

August 8, 2021 by hgpu

HALF: Holistic Auto Machine Learning for FPGAs

Jonas Ney, Dominik Loroch, Vladimir Rybalkin, Nico Weber, Jens Krüger, Norbert Wehn

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Tags: Computer science, Design space exploration, FPGA, HLS, Machine learning, Neural networks

July 4, 2021 by hgpu

Enabling Energy-Efficient DNN Training on Hybrid GPU-FPGA Accelerators

Xin He, Jiawen Liu, Zhen Xie, Hao Chen, Guoyang Chen, Weifeng Zhang, Dong Li

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Tags: Computer science, Deep learning, Design space exploration, FPGA, Hybrid computing, nVidia, OpenCL, Tesla V100

May 2, 2021 by hgpu

Optimal program variant generation for hybrid manycore systems

Cristian Urlea

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Tags: Computer science, Design space exploration, FPGA, Heterogeneous systems, OpenCL, performance portability, Thesis

February 21, 2021 by hgpu

CNN2Gate: An Implementation of Convolutional Neural Networks Inference on FPGAs with Automated Design Space Exploration

Alireza Ghaffari, Yvon Savaria

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Tags: Computer science, Design space exploration, FPGA, Machine learning, Neural networks, OpenCL

December 27, 2020 by hgpu

Design Space Exploration of an OpenCL Based SAXPY Kernel Implementation on FPGAs

Jannatun Naher, Clay Gloster, Shrikant S. Jadhav, Christopher C. Doss

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Tags: Computer science, Design space exploration, FPGA, Linear Algebra, OpenCL

April 19, 2020 by hgpu

Using Machine Learning to Estimate Utilization and Throughput for OpenCL-Based SpMV Implementation on an FPGA

Jannatun Naher, Clay Gloster, Shrikant S. Jadhav, Christopher C. Doss

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Tags: Computer science, Design space exploration, DSP, FPGA, Linear Algebra, Machine learning, OpenCL, Sparse matrix

April 12, 2020 by hgpu

Solving convex optimization problems on FPGA using OpenCL

Martijn Berkers

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Tags: Algorithms, Computer science, Design space exploration, FPGA, OpenCL, Thesis

March 8, 2020 by hgpu

Performance Debugging Frameworks for FPGA High-Level Synthesis

Young-kyu Choi

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Tags: Benchmarking, Computer science, Design space exploration, FPGA, HLS, Performance, Thesis

October 27, 2019 by hgpu

clRNG: an OpenCL based software library containing random number generation functions

A tool set for random number generation on GPUs in R

A Compiler Framework for Optimizing Dynamic Parallelism on GPUs

GPOEO: a micro-intrusive GPU online energy optimization framework for iterative applications

Dynamic GPU Energy Optimization for Machine Learning Training Workloads

CFU Playground: Full-Stack Open-Source Framework for Tiny Machine Learning (tinyML) Acceleration on FPGAs

From Loop Fusion to Kernel Fusion: A Domain-specific Approach to Locality Optimization

System-Level Optimization and Code Generation for Graphics Processors using a Domain-Specific Language

Faster-Mean-Shift-Euc

GPU-accelerated Faster Mean Shift with euclidean distance metrics

Turbo: A constraint solver purely on GPUs (CUDA)

A Variant of Concurrent Constraint Programming on GPU

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high performance computing on graphics processing units: hgpu.org

Studying the Potential of Automatic Optimizations in the Intel FPGA SDK for OpenCL

CFU Playground: Full-Stack Open-Source Framework for Tiny Machine Learning (tinyML) Acceleration on FPGAs

GCN Inference Acceleration using High-Level Synthesis

ScaleHLS: Scalable High-Level Synthesis through MLIR

HALF: Holistic Auto Machine Learning for FPGAs

Enabling Energy-Efficient DNN Training on Hybrid GPU-FPGA Accelerators

Optimal program variant generation for hybrid manycore systems

CNN2Gate: An Implementation of Convolutional Neural Networks Inference on FPGAs with Automated Design Space Exploration

Design Space Exploration of an OpenCL Based SAXPY Kernel Implementation on FPGAs

Using Machine Learning to Estimate Utilization and Throughput for OpenCL-Based SpMV Implementation on an FPGA

Solving convex optimization problems on FPGA using OpenCL

Performance Debugging Frameworks for FPGA High-Level Synthesis

Recent source codes

clRNG: an OpenCL based software library containing random number generation functions

DLRM: An implementation of a deep learning recommendation model

OpenMM: A High Performance Molecular Dynamics Library

Fancier High-Performance API

A Compiler Framework for Optimizing Dynamic Parallelism on GPUs

GPOEO: a micro-intrusive GPU online energy optimization framework for iterative applications

From Loop Fusion to Kernel Fusion: A Domain-specific Approach to Locality Optimization

Faster-Mean-Shift-Euc

Turbo: A constraint solver purely on GPUs (CUDA)

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