Hpc ai500: The methodology, tools, roofline performance models, and metrics for benchmarking hpc ai systems
The recent years witness a trend of applying large-scale distributed deep learning in both
business and scientific computing areas, whose goal is to speed up the training time to …
business and scientific computing areas, whose goal is to speed up the training time to …
MMBench: Benchmarking End-to-End Multi-modal DNNs and Understanding Their Hardware-Software Implications
The explosive growth of various types of big data and advances in AI technologies have
catalyzed a new type of workloads called multi-modal DNNs. Multi-modal DNNs are capable …
catalyzed a new type of workloads called multi-modal DNNs. Multi-modal DNNs are capable …
Coordination-aware assurance for end-to-end machine learning systems: the R3E approach
HL Truong - AI Assurance, 2023 - Elsevier
Concerns of robustness, reliability, resilience, and elasticity in Machine Learning (ML)
systems are important, and they must be considered in trade-off with efficiency factors …
systems are important, and they must be considered in trade-off with efficiency factors …