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+====== Accelerating Data-Intensive Applications with Latency-Tolerant Distributed Shared Memory ======
+==== Jacob Nelson (University of Washington) ====
+== Tuesday, April 7, 4:30 PM to 5:30 PM ==
+== CIC Panther Hollow ==
+===== Abstract =====
+Conventional wisdom suggests that making large-scale distributed
+computations fast requires minimizing the latency of individual
+operations in the computation. In this talk I will discuss a system
+called Grappa that takes the opposite view. Grappa tolerates latency
+by exploiting application parallelism to achieve overall higher throughput.
+Grappa is a modern take on software distributed shared memory for
+in-memory data-intensive applications. Grappa enables users to program
+a cluster as if it were a single, large, non-uniform memory access
+machine. Performance scales up even for applications that have poor
+locality and input-dependent load distribution, as long as sufficient
+parallelism is available.
+===== Bio =====
+Jacob Nelson is a Postdoctoral Research Associate in the Department of
+Computer Science and Engineering at the University of
+Washington. Jacob’s research explores new software and hardware
+techniques to accelerate applications in big data and high-performance
+computing. Jacob defended his Ph.D. at the University of Washington in
+working with Luis Ceze, Mark Oskin, and Simon Kahan.