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Data Remanence and Digital Forensic Investigation for CUDA Graphics Processing Units

X. J. A. Bellekens, G. Paul, J. M. Irvine, C. Tachtatzis, R. C. Atkinson, C. Renfrew, T. Kirkham

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Tags: Computer science, data leak, Data recovery, forensic, GPU, Memory, remanence, vulnerable

May 28, 2016 by xhgpu

GPUstore: Harnessing GPU Computing for Storage Systems in the OS Kernel

Weibin Sun, Robert Ricci, Matthew L. Curry

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Tags: Computer science, CUDA, Data recovery, nVidia, nVidia GeForce GTX 480, Package, Security, Storage system

March 26, 2012 by hgpu

Using Graphics Processors for Parallelizing Hash-based Data Carving

Sylvain Collange, Yoginder Dandass, Marc Daumas, David Defour

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Tags: Computer science, Data recovery, Hashing, nVidia, nVidia GeForce 8500 GT, nVidia GeForce 8600 M GT

November 13, 2010 by hgpu

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Open-source FPGA-ML codesign for the MLPerf Tiny Benchmark

MapReduce for Counting Word Frequencies with MPI and GPUs

CoDL: Efficient CPU-GPU Co-execution for Deep Learning Inference on Mobile Devices

SYCLCOMP Utilities

On the Compilation Performance of Current SYCL Implementations

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CUB: Cooperative primitives for CUDA C++

Onesweep: A Faster Least Significant Digit Radix Sort for GPUs

Simulator and workload generator for Edge-to-Cloud environments

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high performance computing on graphics processing units: hgpu.org

Data Remanence and Digital Forensic Investigation for CUDA Graphics Processing Units

GPUstore: Harnessing GPU Computing for Storage Systems in the OS Kernel

Using Graphics Processors for Parallelizing Hash-based Data Carving

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Open-source FPGA-ML codesign for the MLPerf Tiny Benchmark

MapReduce for Counting Word Frequencies with MPI and GPUs

CoDL: Efficient CPU-GPU Co-execution for Deep Learning Inference on Mobile Devices

SYCLCOMP Utilities

M1 GPUs for (scientific) computations in C++

CUB: Cooperative primitives for CUDA C++

Simulator and workload generator for Edge-to-Cloud environments

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