SFU-Driven Transparent Approximation Acceleration on GPUs (original) (raw)

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Design, Automation & Test in Europe Conference & Exhibition (DATE), 2015, 2015

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An Intermediate Library for Multi-GPUs Computing Skeletons

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2012 IEEE RIVF International Conference on Computing & Communication Technologies, Research, Innovation, and Vision for the Future, 2012

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Specular Effects on the GPU: State of the Art

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NVIDIA's Next-Generation CUDA Compute and Graphics Architecture, Code-Named Fermi, Adds Muscle for Parallel Processing

Gazmend Bojaj

2009

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Architecture for transparent binary acceleration of loops with memory accesses

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Estimation of Volume Rendering Efficiency with GPU in a Parallel Distributed Environment

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Efficient acceleration of sparse MPIE/MoM with graphics processing units

alessandra esposito

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MGSim + MGMark: A Framework for Multi-GPU System Research

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arXiv (Cornell University), 2018

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Memory Performance and Bottlenecks in Multicore and GPU Architectures

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2019 27th Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), 2019

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arXiv (Cornell University), 2023

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Datacenter-Scale Analysis and Optimization of GPU Machine Learning Workloads

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On optimization techniques for the matrix multiplication on hybrid CPU+GPU platforms

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Annals of Multicore and Gpu Programming, 2014

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Effective biclustering on GPU - capabilities and constraints

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PRZEGLĄD ELEKTROTECHNICZNY, 2015

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Transparent Control Flow Transfer between CPU and Accelerators for HPC

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Blaze-DEMGPU: Modular high performance DEM framework for the GPU architecture

Daniel Nico Wilke

SoftwareX, 2016

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Reducing overhead in the Uintah framework to support short-lived tasks on GPU-heterogeneous architectures

Brad Peterson

Proceedings of the 5th International Workshop on Domain-Specific Languages and High-Level Frameworks for High Performance Computing, 2015

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Gpu-based adaptivesubdivision for view-dependent rendering

Jihad El-Sana

2009

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Dynamic Memory Bandwidth Allocation for Real-Time GPU-Based SoC Platforms

Rodolfo Pellizzoni

IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2020

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Spartan: A Sparsity-Adaptive Framework to Accelerate Deep Neural Network Training on GPUs

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Improving the GPU space of computation under triangular domain problems

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