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FLOWER: A Comprehensive Dataflow Compiler for High-Level Synthesis

Puya Amiri, Arsene Perard-Gayot, Richard Membarth, Philipp Slusallek, Roland Leißa, Sebastian Hack

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Tags: Computer science, Computer vision, FPGA, HLS, Image processing, OpenCL

November 21, 2021 by hgpu

Accelerating LBM on a Tightly-Coupled Field Programmable Gate Array

Mateo Vázquez Maceiras

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Tags: cfd, Fluid dynamics, FPGA, HLS, Lattice Boltzmann model, OpenCL, Thesis

October 17, 2021 by hgpu

HLS Portability from Intel to Xilinx: A Case Study

Zhili Xiao, Roger D. Chamberlain, Anthony M. Cabrera

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Tags: Benchmarking, Compilers, Computer science, FPGA, HLS, OpenCL, Package

October 3, 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

StreamBlocks: A compiler for heterogeneous dataflow computing

Endri Bezati, Mahyar Emami, Jörn Janneck, James Larus

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

July 25, 2021 by hgpu

OpenCL FPGA Optimization guided by memory accesses and roofline model analysis applied to tomography acceleration

Daouda Diakite, Nicolas Gac, Maxime Martelli

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Tags: Computed tomography, Computer science, CT, FPGA, HLS, Medicine, OpenCL, Tomography

July 18, 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

Using Workload Characterization to Guide High Performance Graph Processing

Mohamed W. Hassan

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Tags: Computer science, FPGA, Heterogeneous systems, HLS, nVidia, OpenCL, Optimization, Tesla K20, Thesis

May 30, 2021 by hgpu

Accelerating Deep Neural Networks implementation: A survey

Meriam Dhouibi, Ahmed Karim Ben Salem, Afef Saidi, Slim Ben Saoud

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Tags: ASIC, Computer science, Deep learning, FPGA, HLS, Neural networks, OpenCL, Optimization, Performance, survey

March 28, 2021 by hgpu

A Compiler Infrastructure for Accelerator Generators

Rachit Nigam, Samuel Thomas, Zhijing Li, Adrian Sampson

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Tags: Compilers, Computer science, DSL, Hardware Architecture, HLS, Package, Programming Languages

March 14, 2021 by hgpu

hls4ml: An Open-Source Codesign Workflow to Empower Scientific Low-Power Machine Learning Devices

Farah Fahim, Benjamin Hawks, Christian Herwig, James Hirschauer, Sergo Jindariani, Nhan Tran, Luca P. Carloni, Giuseppe Di Guglielmo, Philip Harris, Jeffrey Krupa, Dylan Rankin, Manuel Blanco Valentin, Josiah Hester, Yingyi Luo, John Mamish, Seda Orgrenci-Memik, Thea Aarestaad, Hamza Javed, Vladimir Loncar, Maurizio Pierini, Adrian Alan Pol, Sioni Summers, Javier Duarte, Scott Hauck, Shih-Chieh Hsu, Jennifer Ngadiuba, Mia Liu, Duc Hoang, Edward Kreinar, Zhenbin Wu

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Tags: Algorithms, Computer science, FPGA, HLS, Machine learning, Package, Python

March 14, 2021 by hgpu

Implementation of Autoencoders with Systolic Arrays through OpenCL

Rafael Gadea-Gironés, Vicente Herrero-Bosch, Jose Monzó-Ferrer, Ricardo Colom-Paleros

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Tags: Algorithms, Computer science, Deep learning, FPGA, HLS, Neural networks, OpenCL

January 17, 2021 by hgpu

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

ParaCodex: A Profiling-Guided Autonomous Coding Agent for Reliable Parallel Code Generation and Translation

SeedFold: Scaling Biomolecular Structure Prediction

SeedFold: Scaling Biomolecular Structure Prediction

Tilus: A Tile-Level GPU Kernel Programming Language

Tilus: A Tile-Level GPGPU Programming Language for Low-Precision Computation

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

Memory-Efficient Acceleration of Block Low-Rank Foundation Models on Resource Constrained GPUs

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

CUDA-L2: Surpassing cuBLAS Performance for Matrix Multiplication through Reinforcement Learning

BoltzGen:Toward Universal Binder Design

BoltzGen:Toward Universal Binder Design

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

cuPilot: A Strategy-Coordinated Multi-agent Framework for CUDA Kernel Evolution

MATLAB Tensor Core models

Accurate Models of NVIDIA Tensor Cores

TritonForge: Transform PyTorch Operations into Optimized GPU Kernels with LLMs

TritonForge: Profiling-Guided Framework for Automated Triton Kernel Optimization

RLTune: Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters

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