CPU is a powerful, pervasive, and indispensable platform for running deep learning (DL)
workloads in systems ranging from mobile to extreme-end servers. In this article, we present …

Modern deep learning models have been exploited in various domains, including computer
vision (CV), natural language processing (NLP), search and recommendation. In practical AI …

Today's Internet Services are undergoing fundamental changes and shifting to an intelligent
computing era where AI is widely employed to augment services. In this context, many …

We propose a set of optimization techniques for transforming a generic AI codebase so that
it can be successfully deployed to a restricted serverless environment, without compromising …

The measurable properties of the artifacts or objects in the computer, management, or
finance disciplines are extrinsic, not inherent—dependent on their problem definitions and …

AI benchmarking provides yardsticks for benchmarking, measuring and evaluating
innovative AI algorithms, architecture, and systems. Coordinated by BenchCouncil, this …

Several fundamental changes in technology indicate domain-specific hardware and
software co-design is the only path left. In this context, architecture, system, data …

Deployed AI platforms typically ship with bulky system architectures which present
bottlenecks and a high risk of failure. A serverless deployment can mitigate these factors and …

In this work, we set out to find the answers to the following questions:(1) Where are the
bottlenecks in a state-of-theart architectural simulator?(2) How much faster can architectural …

Modern real-world application scenarios like Internet services consist of a diversity of AI and
non-AI modules with huge code sizes and long and complicated execution paths, which …