Andrea Merlina

Weijia Song, Thiago Garrett, Yuting Yang et al.

Interactive intelligent computing applications are increasingly prevalent, creating a need for AI/ML platforms optimized to reduce per-event latency while maintaining high throughput and efficient resource management. Yet many intelligent applications run on AI/ML platforms that optimize for high throughput even at the cost of high tail-latency. Cascade is a new AI/ML hosting platform intended to untangle this puzzle. Innovations include a legacy-friendly storage layer that moves data with minimal copying and a "fast path" that collocates data and computation to maximize responsiveness. Our evaluation shows that Cascade reduces latency by orders of magnitude with no loss of throughput.

Yuting Yang, Andrea Merlina, Weijia Song et al.

We consider ML query processing in distributed systems where GPU-enabled workers coordinate to execute complex queries: a computing style often seen in applications that interact with users in support of image processing and natural language processing. In such systems, coscheduling of GPU memory management and task placement represents a promising opportunity. We propose Compass, a novel framework that unifies these functions to reduce job latency while using resources efficiently, placing tasks where data dependencies will be satisfied, collocating tasks from the same job (when this will not overload the host or its GPU), and efficiently managing GPU memory. Comparison with other state of the art schedulers shows a significant reduction in completion times while requiring the same amount or even fewer resources. In one case, just half the servers were needed for processing the same workload.

Andrea Merlina, Roman Vitenberg, Vinay Setty

The first generation of blockchain focused on digital currencies and secure storage, management and transfer of tokenized values. Thereafter, the focus has been shifting from currencies to a broader application space. In this paper, we systematically explore marketplace types and properties, and consider the mechanisms required to support those properties through blockchain. We propose a generic and configurable framework for blockchain-based marketplaces, and describe how popular marketplace types, price discovery policies, and other configuration parameters are implemented within the framework by presenting concrete event-based algorithms. Finally, we consider three use cases with widely diverging properties and show how the proposed framework supports them.