Work stealing is an effective load-balancing strategy for multithreading, but when
computations based on it underperform, traditional tools can't explain why. To resolve a …

This paper studies the data locality of the work-stealing scheduling algorithm on hardware-
controlled shared-memory machines. We present lower and upper bounds on the number of …

As small-scale, shared-memory multiprocessors make their way onto desktops, the high-
performance parallel applications that run on these machines will have to live alongside …

Work stealing is a widely-used scheduling technique for parallel processing on multicore.
Each core owns a queue of tasks and avoids idling by stealing tasks from other queues …

Running multithreaded programs in multicore systems has become a common practice for
many application domains. Work stealing is a widely-adopted and effective approach for …

With the rise of multicore computers, parallel applications no longer consist solely of
computational, batch workloads, but also include applications that may, for example, take …

With task parallel models, programmers can easily parallelize divide-and-conquer
algorithms by using nested fork-join structures. Work stealing, which is a popular scheduling …

Work stealing is a popular method of scheduling fine-grained parallel tasks. The
performance of work stealing has been extensively studied, both theoretically and …

Work-stealing is a promising approach for effectively exploiting software parallelism on
parallel hardware. A programmer who uses work-stealing explicitly identifies potential …

Work stealing is a promising approach to constructing multithreaded program runtimes of
parallel programming languages. This paper presents HERMES, an energy-efficient work …