CS Events

PhD Defense Scheduling Methods for Effective Application Scaling
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Speaker: David Domingo

Location : CoRE 301

Committee: 

Professor Sudarsun Kannan (Advisor) 

Professor Santosh Nagarakatte 

Professor Srinivas Narayana 

Professor Minesh Patel 

Professor Junaid Khalid (External Member) 

Event Type: PhD Defense

Abstract: In order to scale performance, modern applications make extensive use of parallelism to maximize utilization of available hardware resources. However, naive use of parallelism often fails to consider potential synchronization, variation in work complexity, heterogeneous resources, as well as caches, leaving unrealized performance on the table. This dissertation presents multiple works that examines how effective modeling and scheduling can manage such complexities and enable applications to scale more effectively against available CPU(s), storage, and memory. In the first part, we show that scheduling speculative work and weighing work based on synchronization potential can help scale a highly stateful file system checker against available CPUs and reduce overall checking runtime. In the second part, we show that dynamic migration of I/O threads across storage devices with effective performance modeling and heuristics can help scale applications against heterogenous storage and increase overall throughput performance. In the last part, we show that scheduling with effective cache latency modeling can maximize cache reuse without compromising latency, helping scale distributed VM allocation against available memory and minimize request latencies. 

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Contact  Professor Sudarsun Kannan

Zoom Link: https://rutgers.zoom.us/j/93102833934?pwd=jN6VYAIE7S6AzeSp1SVMP0ERMjuPbx.1