Turbocharging Rack-Scale In-Memory Computing with Scale-Out NUMA
Speaker: Boris Grot, Lecturer, The University of Edingburgh
Boris Grot is an Assistant Professor in the School of Informatics at the University of Edinburgh. His research seeks to address efficiency bottlenecks and capability shortcomings of processing platforms for big data. His recent accomplishments include an IEEE Micro Top Pick and a Google Faculty Research Award. Grot received his PhD in Computer Science from The University of Texas at Austin and spent two years as a post-doctoral fellow at EPFL.
Web-scale online services mandate fast access to massive quantities of data. In practice, this is accomplished by sharding the datasets across a pool of servers within a datacenter and keeping each shard in the servers' main memory to avoid long-latency disk I/O. Accesses to non-local shards take place over the datacenter network, incurring communication delays that are 20-1000x greater than accesses to local memory. In this talk, I will introduce Scale-Out NUMA -- a rack-scale architecture with an RDMA-inspired programming model that eliminates chief latency overheads of existing networking technologies and reduces the remote memory access latency to a small factor of local DRAM. I will overview key features of Scale-Out NUMA and will describe how it can bridge the semantic gap between software and hardware through integrated support for atomic object reads.