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Combining Belief Propagation and Successive Cancellation List Decoding of Polar Codes on a GPU Platform

Sebastian Cammerer, Benedikt Leible, Matthias Stahl, Jakob Hoydis, Stephan ten Brink

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 980 Ti, Signal processing

September 30, 2016 by hgpu

Efficient dictionary learning implementation on the GPU using OpenCL

Paul Irofti

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Tags: Algorithms, Computer science, Machine learning, OpenCL, Signal processing

September 22, 2016 by hgpu

An Implementation of Real-Time Phased Array Radar Fundamental Functions on a DSP-Focused, High-Performance, Embedded Computing Platform

Xining Yu, Yan Zhang, Ankit Patel, Allen Zahrai, Mark Weber

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Tags: DSP, Filtering, OpenCL, OpenMP, Signal processing

September 10, 2016 by hgpu

Parallel Dictionary Learning Algorithms for Sparse Representations

Paul Irofti

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Tags: ATI, ATI FirePro V8800, Computer science, Data mining, Machine learning, OpenCL, Signal processing, Thesis

September 5, 2016 by hgpu

A Gb/s Parallel Block-based Viterbi Decoder for Convolutional Codes on GPU

Hao Peng, Rongke Liu, Yi Hou, Ling Zhao

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Tags: Algorithms, Computer science, CUDA, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 980, Signal processing

August 4, 2016 by hgpu

A polyphase filter for many-core architectures

Karel Adamek, Jan Novotny, Wes Armour

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Tags: Algorithms, CUDA, Intel Xeon Phi, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 780 Ti, nVidia GeForce GTX 980, nVidia GeForce GTX Titan X, Signal processing, Tesla K40, Tesla K80, Tesla M2090

November 12, 2015 by hgpu

Software Defined Radio over CUDA

Marco Ribero

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Tags: CUDA, nVidia, nVidia GeForce GT 540 M, Signal processing, Thesis

November 3, 2015 by hgpu

Implementation of a Power Efficient Synthetic Aperture Radar Back Projection Algorithm on FPGAs Using OpenCL

David Fan

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Tags: Algorithms, FPGA, Heterogeneous systems, nVidia, OpenCL, SAR, Signal processing, Tesla K40, Thesis

October 18, 2015 by hgpu

PENCIL: A Platform-Neutral Compute Intermediate Language for Accelerator Programming

Riyadh Baghdadi, Ulysse Beaugnon, Albert Cohen, Tobias Grosser, Michael Kruse, Chandan Reddy, Sven Verdoolaege, Adam Betts, Alastair F. Donaldson, Jeroen Ketema, Javed Absar, Sven van Haastregt, Alexey Kravets, Anton Lokhmotov, Robert David, Elnar Hajiyev

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Tags: AMD Radeon R9 285, ARM, ATI, Computer science, DSL, High-level Languages, Image processing, Linear Algebra, nVidia, nVidia GeForce GTX 470, OpenCL, Package, Signal processing

September 15, 2015 by hgpu

GPU-Friendly Local Regression for Voice Conversion

Taylor Berg-Kirkpatrick, Dan Klein

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Tags: Acoustics, CUDA, nVidia, Signal processing, Tesla K40

June 24, 2015 by hgpu

Optimization and Parallelization Methods for the Design of Next-Generation Radio Networks

Lucas Benedicic

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Tags: Algorithms, Cellular automata, Metaheuristics, nVidia, nVidia GeForce GTX 660 Ti, OpenCL, Package, Signal processing, Thesis

June 22, 2015 by hgpu

Efficient FFT mapping on GPU for radar processing application: modeling and implementation

Mohamed Amine Bergach, Emilien Kofman, Robert de Simone, Serge Tissot, Michel Syska

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Tags: FFT, GPGPU, Intel HD 5200, Intel HD Graphics 4000, OpenCL, SAR

June 1, 2015 by Aminems

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

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

GPU plugin for PySCF

Python-Based Quantum Chemistry Calculations with GPU Acceleration

QArray

QArray: a GPU-accelerated constant capacitance model simulator for large quantum dot arrays

Celerity: High-level C++ for Accelerator Clusters

Balancing Tracking Granularity and Parallelism in Many-Task Systems: The Horizons Approach

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

Parallel Gaussian process with kernel approximation in CUDA

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