Modern cloud providers offer dense hardware with multiple cores and large memories, hosted in global platforms. This raises the challenge of implementing high-performance software systems that can effectively scale from a single core to multicore to the globe. Conventional wisdom says that software designed for one scale point needs to be rewritten when scaling up by 10-100x. In contrast, we explore how a system can be architected to scale across many orders of magnitude by design. We explore this challenge in the context of a new key-value store system called Anna: a partitioned, multi-mastered system that achieves high performance and elasticity via waitfree execution and coordination-free consistency. Our design rests on a simple architecture of coordination-free actors that perform state update via merge of lattice-based composite data structures. We demonstrate that a wide variety of consistency models can be elegantly implemented in this architecture with unprecedented consistency, smooth fine-grained elasticity, and performance that far exceeds the state of the art.

Zoom Link: https://cmu.zoom.us/j/562649242

Bio:
Chenggang is a fifth-year Ph.D. student in the RISE Lab at U.C. Berkeley working with Professor Joe Hellerstein. His research interests lie in data-centric systems and distributed systems. He led the development of a high-performance key-value store Anna and is currently building the next-generation serverless computing platform using Anna as the storage backplane.