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High performance pattern matching and data remanence on graphics processing units

X. Bellekens

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Tags: Aho Corasick, Algorithms, amazon, BMH, CUDA, Digital Forensic, forensic, GPU, pattern matching, PFAC, remanence, Sequence matching, String matching, Suffix Tree, Tesla K20, Tesla K20c

November 22, 2016 by xhgpu

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

ATTUNE: Agentic Throughput Tuning for LLM Training

ATTUNE: Agentic Throughput Tuning for LLM Training

HPCAgent-Bench: A Framework for Sound Benchmarking of Code-Optimizing Agents, Harnesses, and Skills

HPCAgent-Bench: A Framework for Sound Benchmarking of Code-Optimizing Agents, Harnesses, and Skills

Brian2 Atlas

A Unified Intermediate Representation and Execution Architecture for Heterogeneous and Distributed Neural Simulation

AgentGarten: Code Worlds for Evolving Agents

AgentGarten: Code Worlds for Evolving Agents

KernelLens: Automated Triton-to-C++ Compiler for Enterprise Inference Runtimes

KernelLens: Deploying Triton Kernels to C++ Inference Engines

KernelZero: Co-Evolving Proposer and Coder for Continuously Improved GPU Kernel Generation

KernelZero: Co-Evolving Proposer and Coder for Continuously Improved GPU Kernel Generation

Introduction to Computer Vision

Introduction to Computer Vision

ACT: Accelerator Compiler Toolkit

Automatically Generating ML Compiler Backends from Tensor Accelerator ISA Descriptions

pytest-gpu-proof: A Simple Pytest Extension for Local GPU Code Testing

pytest-gpu-proof: Enabling Cloud-CPU Continuous Integration for GPU Code with Local GPU Attestation

Accelerating the Mitigation of LLM Inference Nondeterminism Across GPU Architectures

Accelerating the Mitigation of LLM Inference Nondeterminism Across GPU Architectures

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