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MKPipe: A Compiler Framework for Optimizing Multi-Kernel Workloads in OpenCL for FPGA

Ji Liu, Abdullah-Al Kafi, Xipeng Shen, Huiyang Zhou

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Tags: Compilers, Computer science, FPGA, nVidia, nVidia GeForce RTX 2080, OpenCL, Performance

February 9, 2020 by hgpu

Hardware/Software Co-Design for Data-Intensive Genomics Workloads

Nicola Cadenelli

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Tags: Algorithms, Computer science, FPGA, nVidia, OpenCL, performance portability, Tesla K40, Thesis

January 26, 2020 by hgpu

Hardware Implementation and Quantization of Tiny-Yolo-v2 using OpenCL

Yap June Wai, Zulkalnain bin Mohd Yussof, Sani Irwan bin Md Salim

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Tags: Computer science, Computer vision, Deep learning, DSP, FPGA, Neural networks, OpenCL

January 19, 2020 by hgpu

An Efficient Hardware Accelerator for Structured Sparse Convolutional Neural Networks on FPGAs

Chaoyang Zhu, Kejie Huang, Shuyuan Yang, Ziqi Zhu, Hejia Zhang, Haibin Shen

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Tags: Artificial intelligence, Computer science, Deep learning, FPGA, Neural networks

January 12, 2020 by hgpu

Fast Turnaround HLS Debugging using Dependency Analysis and Debug Overlays

Al-Shahna Jamal, Eli Cahill, Jeffrey Goeders,Steven J.E. Wilton

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Tags: Computer science, FPGA, HLS

January 12, 2020 by hgpu

LLVM-based automation of memory decoupling for OpenCL applications on FPGAs

Arnab A Purkayastha, Samuel Rogers, Suhas A Shiddhibhabi, Hamed Tabkhi

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Tags: Computer science, FPGA, LLVM, OpenCL, Package

January 5, 2020 by hgpu

Accelerating Molecular Docking by Parallelized Heterogeneous Computing – A Case Study of Performance, Quality of Results, and Energy-Efficiency using CPUs, GPUs, and FPGAs

Leonardo Solis Vasquez

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Tags: AMD Radeon RX Vega 56, ATI, Computer science, FPGA, Heterogeneous systems, Macromolecule, nVidia, OpenCL, Package, Physics, Tesla V100, Thesis

December 29, 2019 by hgpu

The BondMachine toolkit: Enabling Machine Learning on FPGA

Mirko Mariotti, Loriano Storchi, Daniele Spiga, Davide Salomoni, Tommaso Boccali, Daniele Bonacorsi

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Tags: Computer science, FPGA, Go, Machine learning

December 8, 2019 by hgpu

FBLAS: Streaming Linear Algebra Kernels on FPGA

Tiziano De Matteis, Johannes de Fine Licht, Torsten Hoefler

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Tags: BLAS, Computer science, FPGA, Linear Algebra, OpenCL, Package

December 1, 2019 by hgpu

FeCaffe: FPGA-enabled Caffe with OpenCL for Deep Learning Training and Inference on Intel Stratix 10

Ke He, Bo Liu, Yu Zhang, Andrew Ling, Dian Gu

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Tags: Caffe, Computer science, Deep learning, FPGA, Neural networks, OpenCL

November 24, 2019 by hgpu

Deep Learning Based FPGA-CPU Acceleration

R. Luis Jalabert

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Tags: Code generation, Computer science, Deep learning, FPGA, Machine learning, Neural networks, Package, Thesis

November 17, 2019 by hgpu

A Highly Parameterizable Framework for Conditional Restricted Boltzmann Machine Based Workloads Accelerated With FPGAs and OpenCL

Zoran Jaksic, Nicola Cadenelli, David Buchaca Prats, Jorda Polo, Josep Lluis Berral Garcia, David Carrera Perez

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Tags: Computer science, FPGA, HLS, Linear Algebra, Matrix multiplication, Neural networks, OpenCL

November 17, 2019 by hgpu

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

ParallelKittens: Systematic and Practical Simplification of Multi-GPU AI Kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

Iris: First-Class Multi-GPU Programming Experience in Triton

HipKittens: Fast and Furious AMD Kernels

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

pplx-garden: Perplexity open source garden for inference technology

RDMA Point-to-Point Communication for LLM Systems

LC Framework

Characterizing the Performance of Parallel Data-Compression Algorithms across Compilers and GPUs

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high performance computing on graphics processing units: hgpu.org

MKPipe: A Compiler Framework for Optimizing Multi-Kernel Workloads in OpenCL for FPGA

Hardware/Software Co-Design for Data-Intensive Genomics Workloads

Hardware Implementation and Quantization of Tiny-Yolo-v2 using OpenCL

An Efficient Hardware Accelerator for Structured Sparse Convolutional Neural Networks on FPGAs

Fast Turnaround HLS Debugging using Dependency Analysis and Debug Overlays

LLVM-based automation of memory decoupling for OpenCL applications on FPGAs

Accelerating Molecular Docking by Parallelized Heterogeneous Computing – A Case Study of Performance, Quality of Results, and Energy-Efficiency using CPUs, GPUs, and FPGAs

The BondMachine toolkit: Enabling Machine Learning on FPGA

FBLAS: Streaming Linear Algebra Kernels on FPGA

FeCaffe: FPGA-enabled Caffe with OpenCL for Deep Learning Training and Inference on Intel Stratix 10

Deep Learning Based FPGA-CPU Acceleration

A Highly Parameterizable Framework for Conditional Restricted Boltzmann Machine Based Workloads Accelerated With FPGAs and OpenCL

Recent source codes

NVIDIA Nemotron Parse 1.1

ThunderKittens: Tile primitives for speedy kernels

Iris: AMD RAD's multi-GPU Triton-based framework for seamless multi-GPU programming

HipKittens: Fast and Furious AMD Kernels

Fortran xDSL dialects

mt4g: Memory Topology 4 GPUs

Falcon: GPU-Based Floating-point Adaptive Lossless Compression

CudaForge: An Agent Framework with Hardware Feedback for CUDA Kernel Optimization

pplx-garden: Perplexity open source garden for inference technology

LC Framework

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