Abstract:
The memory system has historically been a primary performance determinant for server-grade computers. The multi-faceted challenges it poses is commonly referred to as the “memory wall”, referring to rigid capacity, bandwidth, and cost constraints. Current technological trends motivate a memory architecture rethink by leveraging serial interfaces, opening opportunities to overcome current limitations. Specifically, these opportunities are embodied by the emerging Compute Express Link (CXL) technology, which is garnering widespread adoption in the industry. CXL is well-positioned to revolutionize the way server systems are built and deployed, as it enables new capabilities in memory system design. CXL-centric or CXL-augmented memory systems bear characteristics that cater well to the growing demands of modern workloads. This talk will focus on two new CXL-centric memory systems for server architectures. First, we will see how a CXL-only memory system can drastically benefit modern manycore CPUs handling bandwidth-intensive workloads, despite the CXL interface’s seemingly prohibitive latency premium. Second, we will study how CXL’s memory pooling capability can be leveraged to accelerate workloads with little data locality on large-scale multi-socket NUMA systems. Both architectural approaches promise performance gains of up to 3x for their respective workload domain.

Bio:
Alexandros (Alex) Daglis is an Assistant Professor of Computer Science at Georgia Tech. Daglis’ research interests lie in computer architecture, with specific interests in datacenter architectures, network-compute co-design, and memory systems. His research has been supported by the NSF, IARPA, Speculative Technologies, Samsung, and Intel Corporation, and routinely appears at top-tier computer architecture venues such as ISCA, MICRO, ASPLOS, and HPCA. Daglis is a recipient of the NSF CAREER award, a Google Faculty Research Award, and a Georgia Tech Junior Faculty Teaching Award, and his PhD thesis (EPFL, 2018) was recognized with an ACM SIGARCH/IEEE CS TCCA Outstanding Dissertation Honorable Mention.