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Directive-Based, High-Level Programming and Optimizations for High-Performance Computing with FPGAs

Jacob Lambert, Seyong Lee, Jungwon Kim, Jeffrey S. Vetter, Allen D. Malony

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Tags: Computer science, FPGA, nVidia, OpenACC, OpenCL, Tesla K40

July 1, 2018 by hgpu

RAPIDNN: In-Memory Deep Neural Network Acceleration Framework

Mohsen Imani, Mohammad Samragh, Yeseong Kim, Saransh Gupta, Farinaz Koushanfar, Tajana Rosing

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Tags: AMD Radeon HD 7970, ATI, CNN, Computer science, Deep learning, FPGA, Hardware Architecture, Neural networks, OpenCL

June 20, 2018 by hgpu

Combining Multiple Optimised FPGA-based Pulsar Search Modules Using OpenCL

Haomiao Wang, Prabu Thiagaraj, Oliver Sinnen

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Tags: Astrophysics, FPGA, OpenCL, Signal processing

June 17, 2018 by hgpu

Acceleration of k-Nearest Neighbor and SRAD Algorithms Using Intel FPGA SDK for OpenCL

Liyuan Liu

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Tags: Algorithms, Computer science, FPGA, Machine learning, Nearest neighbour, OpenCL, Sorting, Thesis

June 17, 2018 by hgpu

Efficient Large-scale Approximate Nearest Neighbor Search on OpenCL FPGA

Jialiang Zhang, Soroosh Khoram, Jing Li

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Tags: Computer science, FPGA, Nearest neighbour, nVidia, nVidia GeForce GTX Titan XP, OpenCL

June 13, 2018 by hgpu

A High-efficiency FPGA-based Accelerator for Convolutional Neural Networks using Winograd Algorithm

Y. Huang, J. Shen, Z. Wang, M. Wen, C. Zhang

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Tags: Computational Complexity, Computer science, Computer vision, Deep learning, FPGA, HLS, Neural networks

June 9, 2018 by hgpu

Design of FPGA-Based Accelerator for Convolutional Neural Network under Heterogeneous Computing Framework with OpenCL

Li Luo, Yakun Wu, Fei Qiao, Yi Yang, Qi Wei, Xiaobo Zhou, Yongkai Fan, Shuzheng Xu, Xinjun Liu, Huazhong Yang

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

June 2, 2018 by hgpu

FPGA-based Acceleration of FT Convolution for Pulsar Search Using OpenCL

Haomiao Wang, Prabu Thiagaraj, Oliver Sinnen

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Tags: AMD Radeon R7 370, Astrophysics, ATI, FPGA, OpenCL

June 2, 2018 by hgpu

Transformations of High-Level Synthesis Codes for High-Performance Computing

Johannes de Fine Licht, Simon Meierhans, Torsten Hoefler

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Tags: Computer science, FPGA, HLS, OpenCL

May 26, 2018 by hgpu

Parallel Programming for FPGAs

Ryan Kastner, Janarbek Matai, Stephen Neuendorffer

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Tags: Book, Computer science, FPGA, HLS

May 12, 2018 by hgpu

Efficient Hardware Acceleration on SoC-FPGA with OpenCL

Susmitha Gogineni

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

May 12, 2018 by hgpu

Tiramisu: A Code Optimization Framework for High Performance Systems

Riyadh Baghdadi, Jessica Ray, Malek Ben Romdhane, Emanuele Del Sozzo, Patricia Suriana, Shoaib Kamil, Saman Amarasinghe

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Tags: Algorithms, Code generation, Computer science, CUDA, Distributed computing, FPGA, Heterogeneous systems, Linear Algebra, LLVM, MPI, nVidia, OpenMPI, Tesla K40

May 5, 2018 by hgpu

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

SimSYCL: A SYCL Implementation Targeting Development, Debugging, Simulation and Conformance

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

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

94% on CIFAR-10 in 3.29 Seconds on a Single GPU

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

See all packages

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high performance computing on graphics processing units: hgpu.org

Directive-Based, High-Level Programming and Optimizations for High-Performance Computing with FPGAs

RAPIDNN: In-Memory Deep Neural Network Acceleration Framework

Combining Multiple Optimised FPGA-based Pulsar Search Modules Using OpenCL

Acceleration of k-Nearest Neighbor and SRAD Algorithms Using Intel FPGA SDK for OpenCL

Efficient Large-scale Approximate Nearest Neighbor Search on OpenCL FPGA

A High-efficiency FPGA-based Accelerator for Convolutional Neural Networks using Winograd Algorithm

Design of FPGA-Based Accelerator for Convolutional Neural Network under Heterogeneous Computing Framework with OpenCL

FPGA-based Acceleration of FT Convolution for Pulsar Search Using OpenCL

Transformations of High-Level Synthesis Codes for High-Performance Computing

Parallel Programming for FPGAs

Efficient Hardware Acceleration on SoC-FPGA with OpenCL

Tiramisu: A Code Optimization Framework for High Performance Systems

Recent source codes

SimSYCL: Synchronous, single-threaded, library-only SYCL implementation for debugging and verification

GPU plugin for PySCF

QArray

Celerity: High-level C++ for Accelerator Clusters

gpu_tracker: Context manager and CLI that tracks the computational-resource-usage of a code block or shell command, particularly the GPU usage

CIFAR-10 Airbench: 94% on CIFAR-10 in 3.29 second

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

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