Show simple item record

dc.contributor.authorKrommydas, Konstantinosen
dc.date.accessioned2017-05-04T08:00:41Zen
dc.date.available2017-05-04T08:00:41Zen
dc.date.issued2017-05-03en
dc.identifier.othervt_gsexam:9379en
dc.identifier.urihttp://hdl.handle.net/10919/77582en
dc.description.abstractThe proliferation of a diverse set of heterogeneous computing platforms in conjunction with the plethora of programming languages and optimization techniques on each language for each underlying architecture exacerbate widespread adoption of such platforms. This is especially true for novice programmers and the non-technical-savvy masses that are largely precluded from enjoying the advantages of high-performance computing. Moreover, different groups within the heterogeneous computing community (e.g., hardware architects, tool developers, and programmers) are presented with new challenges with respect to performance, programmability, and portability (or the three P's) of heterogeneous computing. In this work we discuss such challenges and identify benchmarking techniques based on computation and communication patterns as an appropriate means for the systematic evaluation of heterogeneous computing with respect to the three P's. Our proposed approach is based on OpenCL implementations of the Berkeley dwarfs. We use our benchmark suite (OpenDwarfs) in characterizing performance of state-of-the-art parallel architectures, and as the main component of a methodology (Telescoping Architectures) for identifying trends in future heterogeneous architectures. Furthermore, we employ OpenDwarfs in a multi-faceted study on the gaps between the three P's in the context of the modern heterogeneous computing landscape. Our case-study spans a variety of compilers, languages, optimizations, and target architectures, including the CPU, GPU, MIC, and FPGA. Based on our insights, and extending aspects of prior research (e.g., in compilers, programming languages, and auto-tuning), we propose the introduction of grid-based data structures as the basis of programming frameworks and present a prototype unified framework (GLAF) that encompasses a novel visual programming environment with code generation, auto-parallelization, and auto-tuning capabilities. Our results, which span scientific domains, indicate that our holistic approach constitutes a viable alternative towards enhancing the three P's and further democratizing heterogeneous, parallel computing for non-programming-savvy audiences, and especially domain scientists.en
dc.format.mediumETDen
dc.publisherVirginia Techen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectPerformanceen
dc.subjectProgrammabilityen
dc.subjectHeterogeneous Architecturesen
dc.subjectParallel Computingen
dc.subjectProgramming Frameworken
dc.titleTowards Enhancing Performance, Programmability, and Portability in Heterogeneous Computingen
dc.typeDissertationen
dc.contributor.departmentComputer Scienceen
dc.description.degreePh. D.en
thesis.degree.namePh. D.en
thesis.degree.leveldoctoralen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.disciplineComputer Science and Applicationsen
dc.contributor.committeechairFeng, Wu-Chunen
dc.contributor.committeememberSasanka, Ruchiraen
dc.contributor.committeememberTilevich, Elien
dc.contributor.committeememberButt, Ali R.en
dc.contributor.committeememberCao, Yongen


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record