11 citations · 19 across the 5 of their papers we have counts for
6 papers
Operationalizing Property-Based Testing for Data-Intensive Scalable Computing Systems
Yaoxuan Wu, Ingrid Lee, Ahmad Humayun +2
While fuzzing effectively catches crashes, its shallow oracles often miss semantic drifts and optimization-related errors in data-intensive scalable computing (DISC) frameworks. Pr…
Responsive Parallelism with Synchronization
Stefan K. Muller, Kyle Singer, Devyn Terra Keeney +4
Many concurrent programs assign priorities to threads to improve responsiveness. When used in conjunction with synchronization mechanisms such as mutexes and condition variables, h…
Responsive Parallelism with Futures and State
Stefan K. Muller, Kyle Singer, Noah Goldstein +3
Motivated by the increasing shift to multicore computers, recent work has developed language support for responsive parallel applications that mix compute-intensive tasks with late…
Reduced I/O Latency with Futures
Kyle Singer, Kunal Agrawal, I-Ting Angelina Lee
Task parallelism research has traditionally focused on optimizing computation-intensive applications. Due to the proliferation of commodity parallel processors, there has been rece…
Efficient Race Detection with Futures
Robert Utterback, Kunal Agrawal, Jeremy Fineman +1
This paper addresses the problem of provably efficient and practically good on-the-fly determinacy race detection in task parallel programs that use futures. Prior works determinac…
A NUMA-Aware Provably-Efficient Task-Parallel Platform Based on the Work-First Principle
Justin Deters, Jiaye Wu, Yifan Xu +1
Task parallelism is designed to simplify the task of parallel programming. When executing a task parallel program on modern NUMA architectures, it can fail to scale due to the phen…