Irregular and dynamic parallel applications pose significant challenges to achieving
scalable performance on large-scale multicore clusters. These applications often require …

The non-blocking work-stealing algorithm of Arora, Blumofe, and Plaxton (henceforth ABP
work-stealing) is on its way to becoming the multiprocessor load balancing technology of …

Work stealing has proven to be an effective method for scheduling parallel programs on
multicore computers. To achieve high performance, work stealing distributes tasks between …

Building correct and efficient concurrent algorithms is known to be a difficult problem of
fundamental importance. To achieve efficiency, designers try to remove unnecessary and …

The recent addition of task parallelism to the OpenMP shared memory API allows
programmers to express concurrency at a high level of abstraction and places the burden of …

Load balancing is a technique which allows efficient parallelization of irregular workloads,
and a key component of many applications and parallelizing runtimes. Work-stealing is a …

Multiprocessor scheduling in a shared multiprogramming environment can be structured as
two-level scheduling, where a kernel-level job scheduler allots processors to jobs and a …

Work-stealing is an efficient method to implement load balancing in fine-grained task
parallelism. Typically, concurrent deques are used for this purpose. A disadvantage of many …

It has been shown that any nonblocking algorithm for work-stealing in the standard
asynchronous shared memory model of computation must use expensive Read-After-Write …

There has been and is a tremendous amount of research on the topic of ray tracing, spurred
by the relatively recent advent of real-time ray tracing and the inevitable appearance of …