high performance computing on graphics processing units: hgpu.org

hgpu.org » FPGA

Sorting on FPGAs using Merge Trees

Nikola Samardzic

View

Download (PDF)

Tags: Algorithms, Computer science, FPGA, Sorting

July 21, 2019 by hgpu

On the Portability of CPU-Accelerated Applications via Automated Source-to-Source Translation

Paul Sathre, Mark Gardner, Wu-chun Feng

View

Download (PDF)

Source codes

Tags: AMD FirePro S9150, ATI, Compilers, Computer science, CUDA, FPGA, nVidia, OpenCL, Package, performance portability, Tesla K80

July 14, 2019 by hgpu

Exploring Portability and Performance of OpenCL FPGA Kernels on Intel HARPv2

Anthony M. Cabrera, Roger D. Chamberlain

View

Download (PDF)

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

View

Download (PDF)

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

View

Download (PDF)

Source codes

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

View

Download (PDF)

Tags: Computer science, FPGA, OpenCL, Performance

June 9, 2019 by hgpu

The Accelerator Wall: Limits of Chip Specialization

Adi Fuchs, David Wentzlaff

View

Download (PDF)

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

View

Download (PDF)

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

View

Download (PDF)

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

View

Download (PDF)

Source codes

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

View

Download (PDF)

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

May 19, 2019 by hgpu

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Dr. Kernel: Reinforcement Learning Done Right for Triton Kernel Generations

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Generating Literature-Driven Scientific Theories at Scale

See all packages

* * *

high performance computing on graphics processing units: hgpu.org

Sorting on FPGAs using Merge Trees

On the Portability of CPU-Accelerated Applications via Automated Source-to-Source Translation

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

Recent source codes

CL4SE: A Context Learning Benchmark For Software Engineering Tasks

CodeScaler: Scaling Code LLM Training and Test-Time Inference via Execution-Free Reward Models

A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5

DICE: Diffusion Large Language Models Excel at Generating CUDA Kernels

KernelGYM & Dr. Kernel: A distributed GPU environment and a collection of RL training methods to support RL for Kernel Generations

Vortex-Optimized Light-weight Toolchain (VOLT)

SciDef: Automated Definition Extraction from Scientific Literature

bioagent-bench: Benchmark for evaluating LLM agents in bioinformatics

Benchmark suite for LLM inference on NVIDIA consumer GPUs

Theorizer: from the paper Generating Literature-Driven Scientific Discoveries at Scale

Most viewed papers (last 30 days)