GPUs are parallel devices that are able to run thousands of independent threads concurrently. Traditional GPU programs are data-parallel, requiring little to no communication, i.e. synchronisation, between threads. However, classical concurrency in …
Graphics Processing Units (GPUs) are highly parallel shared memory microprocessors, and as such, they are prone to the same concurrency considerations as their traditional multicore CPU counterparts. In this thesis, we consider shared memory …
With the widespread use of GPUs, it is important to ensure that programmers have a clear understanding of their shared memory consistency model i.e. what values can be read when issued concurrently with writes. While memory consistency has been …