GPEmu: A GPU emulator for rapid, low-cost deep learning prototyping [pdf]

原始链接: https://vldb.org/pvldb/vol18/p1919-wang.pdf

This PDF data contains information about hyperlinks (annotations) within a document. Each entry defines a link with properties such as its location (Rect), color (C), and destination (Dest). The destinations point to various online resources, including: * Cloud platforms like AWS, Azure, and GCP, specifically related to GPU pricing and availability. * Cloud computing infrastructure projects like Chameleon and CloudLab. * Research papers and websites related to data management and optimization techniques for machine learning, such as: * Distributed data processing (DPP) * Caching strategies (CacheW, MLCoomStore, DLCache, SiloD) * Data locality (Locality-Aware) * Resource management and scheduling (Salus, Synergy) * High-performance data loading (AlloX, FastFlow, Gandiva, Lobster, FFCV, DataStall, EfficientTrain, GoldMiner, DeepIO, Muri) * Issues related to GPU availability and quota management on cloud platforms. The data suggests the document focuses on cloud-based machine learning infrastructure, resource management, and optimization strategies for improving performance and addressing challenges like GPU scarcity and data access bottlenecks.

原文

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