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Soft GPGPUs for Embedded FPGAs: An Architectural Evaluation

Kevin Andryc, Tedy Thomas, Russell Tessier

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Tags: Benchmarking, Computer science, CUDA, DSP, FPGA

June 22, 2016 by hgpu

Combinatorial Optimization of Work Distribution on Heterogeneous Systems

Suejb Memeti, Sabri Pllana

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Tags: Computer science, Heterogeneous systems, Intel Xeon Phi, Machine learning, Optimization

June 21, 2016 by hgpu

cltorch: a Hardware-Agnostic Backend for the Torch Deep Neural Network Library, Based on OpenCL

Hugh Perkins

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Tags: Algorithms, CNN, Computer science, Deep learning, Machine learning, Neural networks, nVidia, nVidia GRID K520, OpenCL, Package

June 21, 2016 by hgpu

YodaNN: An Ultra-Low Power Convolutional Neural Network Accelerator Based on Binary Weights

Renzo Andri, Lukas Cavigelli, Davide Rossi, Luca Benini

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Tags: Computer science, Computer vision, Deep learning, Hardware Architecture, Neural networks

June 21, 2016 by hgpu

Acceleration of Statistical Detection of Zero-day Malware in the Memory Dump Using CUDA-enabled GPU Hardware

Igor Korkin, Iwan Nesterow

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Tags: Computer science, CUDA, nVidia, Security

June 21, 2016 by hgpu

A Parallel Algorithm for LZW Decompression, with GPU Implementation

Shunji Funasaka, Koji Nakano, Yasuaki Ito

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Tags: Compression, CUDA, nVidia, nVidia GeForce GTX 980

June 21, 2016 by funasaka

Electric potential and field calculation of charged BEM triangles and rectangles by Gaussian cubature

Ferenc Gluck, Daniel Hilk

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Tags: Computational Physics, nVidia, OpenCL, Physics, Tesla K40

June 16, 2016 by hgpu

NCAM: Near-Data Processing for Nearest Neighbor Search

Vincent T. Lee, Carlo C. del Mundo, Armin Alaghi, Luis Ceze, Mark Oskin, Ali Farhadi

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Tags: Computer science, CUDA, Machine learning, Nearest neighbour, nVidia, nVidia GeForce GTX Titan X, nVidia Jetson TK1

June 16, 2016 by hgpu

Splotch: porting and optimizing for the Xeon Phi

Timothy Dykes, Claudio Gheller, Marzia Rivi, Mel Krokos

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Tags: Computer science, CUDA, Intel Xeon Phi, Numerical simulation, nVidia, OpenCL, Package, Tesla K20, Visualization

June 16, 2016 by hgpu

Omnivore: An Optimizer for Multi-device Deep Learning on CPUs and GPUs

Stefan Hadjis, Ce Zhang, Ioannis Mitliagkas, Christopher Re

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Tags: Computer science, CUDA, Deep learning, Machine learning, Neural networks, nVidia, nVidia GeForce GTX Titan X

June 16, 2016 by hgpu

Multi-Tenant Virtual GPUs for Optimising Performance of a Financial Risk Application

Javier Prades, Blesson Varghese, Carlos Reano, Federico Silla

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Tags: Computer science, CUDA, Finance, nVidia, Tesla K20

June 16, 2016 by hgpu

Performance-Portable Many-Core Plasma Simulations: Porting PIConGPU to OpenPower and Beyond

Erik Zenker, Rene Widera, Axel Hubl, Guido Juckeland, Andreas Knupfer, Wolfgang E. Nagel, Michael Bussmann

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Tags: Computer science, CUDA, Heterogeneous systems, nVidia, OpenMP, Package, Particle-in-cell methods, Physics, Plasma physics, Programming techniques, Tesla K80

June 14, 2016 by hgpu

AutoPass: Evidence-Guided LLM Agents for Compiler Performance Tuning

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CUDA Kernel Fusion Benchmarks

Analyzing the Impact of Kernel Fusion on GPU Tensor Operation Performance: A Systematic Performance Study

IntelliKit: Agent-first tooling for AMD hardware

Kerncap: Automated Kernel Extraction and Isolation for AMD GPUs

DITRON: Distributed Compiler based on Triton for Parallel Systems

DITRON: Distributed Multi-level Tiling Compiler for Parallel Tensor Programs

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Evaluating CUDA Tile for AI Workloads on Hopper and Blackwell GPUs

Device Virtual Machine (DVM)

DVM: Real-Time Kernel Generation for Dynamic AI Models

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high performance computing on graphics processing units: hgpu.org

Applications

Soft GPGPUs for Embedded FPGAs: An Architectural Evaluation

Combinatorial Optimization of Work Distribution on Heterogeneous Systems

cltorch: a Hardware-Agnostic Backend for the Torch Deep Neural Network Library, Based on OpenCL

YodaNN: An Ultra-Low Power Convolutional Neural Network Accelerator Based on Binary Weights

Acceleration of Statistical Detection of Zero-day Malware in the Memory Dump Using CUDA-enabled GPU Hardware

A Parallel Algorithm for LZW Decompression, with GPU Implementation

Electric potential and field calculation of charged BEM triangles and rectangles by Gaussian cubature

NCAM: Near-Data Processing for Nearest Neighbor Search

Splotch: porting and optimizing for the Xeon Phi

Omnivore: An Optimizer for Multi-device Deep Learning on CPUs and GPUs

Multi-Tenant Virtual GPUs for Optimising Performance of a Financial Risk Application

Performance-Portable Many-Core Plasma Simulations: Porting PIConGPU to OpenPower and Beyond

Recent source codes

AutoPass: Evidence-Guided LLM Agents for Compiler Performance Tuning

Probe-and-Refine Tuning of Repository Guidance for AI Coding Agents

CUDAnalyst (CUDA + Analyst)

CodegenBench

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CUDA Kernel Fusion Benchmarks

IntelliKit: Agent-first tooling for AMD hardware

DITRON: Distributed Compiler based on Triton for Parallel Systems

CuTile Benchmark Suite: Performance and Productivity Tradeoffs for GPU Kernel Programming on Blackwell Architecture

Device Virtual Machine (DVM)

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