Exploiting Nested Parallelism on Heterogeneous Processors

dc.contributor.advisorYeung, Donalden_US
dc.contributor.authorZuzak, Michaelen_US
dc.contributor.departmentElectrical Engineeringen_US
dc.contributor.publisherDigital Repository at the University of Marylanden_US
dc.contributor.publisherUniversity of Maryland (College Park, Md.)en_US
dc.date.accessioned2016-06-22T06:00:55Z
dc.date.available2016-06-22T06:00:55Z
dc.date.issued2016en_US
dc.description.abstractHeterogeneous computing systems have become common in modern processor architectures. These systems, such as those released by AMD, Intel, and Nvidia, include both CPU and GPU cores on a single die available with reduced communication overhead compared to their discrete predecessors. Currently, discrete CPU/GPU systems are limited, requiring larger, regular, highly-parallel workloads to overcome the communication costs of the system. Without the traditional communication delay assumed between GPUs and CPUs, we believe non-traditional workloads could be targeted for GPU execution. Specifically, this thesis focuses on the execution model of nested parallel workloads on heterogeneous systems. We have designed a simulation flow which utilizes widely used CPU and GPU simulators to model heterogeneous computing architectures. We then applied this simulator to non-traditional GPU workloads using different execution models. We also have proposed a new execution model for nested parallelism allowing users to exploit these heterogeneous systems to reduce execution time.en_US
dc.identifierhttps://doi.org/10.13016/M28B6V
dc.identifier.urihttp://hdl.handle.net/1903/18305
dc.language.isoenen_US
dc.subject.pqcontrolledComputer engineeringen_US
dc.subject.pquncontrolledHeterogeneous Execution Modelsen_US
dc.subject.pquncontrolledHeterogeneous Processorsen_US
dc.subject.pquncontrolledMultigrain Parallelismen_US
dc.subject.pquncontrolledNested Parallelismen_US
dc.titleExploiting Nested Parallelism on Heterogeneous Processorsen_US
dc.typeThesisen_US

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Zuzak_umd_0117N_17051.pdf
Size:
930.8 KB
Format:
Adobe Portable Document Format