2026-09-21T01:29:21Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/116159 2023-07-11 col_2142_5131 col_2142_10761 com_2142_5130 com_2142_10755 com_2142_234

Kale, Laxmikant Kale, Laxmikant Amato, Nancy Padua, David Chamberlain, Brad 2022-08 application/pdf en text Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-11-15 without embargo terms The student, Justin Szaday, accepted the attached license on 2022-06-30 at 17:31. The student, Justin Szaday, submitted this Dissertation for approval on 2022-06-30 at 17:35. This Dissertation was approved for publication on 2022-07-06 at 16:25. DSpace SAF Submission Ingestion Package generated from Vireo submission #18071 on 2022-11-15 at 17:37:34 Building blocks for high-performance languages Szaday, Justin Josef 2022-07-06 Compilers Programming Languages High-performance Computing Runtime Adaptivity As machine complexity and diversity rise, the importance of high-level abstractions to the high-performance computing ecosystem rises. These tools, like adaptive runtimes and domain-specific or general-purpose languages, promote developer productivity and performance portability, lowering the barrier to building large-scale, high-performance parallel applications. However, their development and maintenance costs can be discouragingly high, relegating us to the use of classical, low-level tools. Observing this, we propose that a language framework with high-level constructs built on a rich runtime system can significantly improve the productivity of language authors. To explore this hypothesis, we designed and implemented such a framework, EIR, then targeted it with an extensible language, Ergoline. Within Ergoline, we embedded several DSLs derived from past works built on the underlying RTS, Charm++. We explored code reuse among them and offered shared optimizations within EIR. To close semantic gaps between Charm++ and EIR, we developed Hypercomm—a suite of optimized abstractions. Through our experiences developing these tools, we conclude that our approach can offer performance and productivity benefits to language authors and their users alike Thesis eng https://hdl.handle.net/2142/116159 Copyright 2022 Justin Szaday Ph.D. Dissertation Computer Science University of Illinois at Urbana-Champaign Computer Science