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        <datestamp>2025-10-20</datestamp>
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          <dc:description>Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-19 without embargo terms</dc:description>
          <dc:description>The student, Russel Arbore, accepted the attached license on 2025-04-15 at 20:55.</dc:description>
          <dc:description>The student, Russel Arbore, submitted this Thesis for approval on 2025-04-15 at 21:01.</dc:description>
          <dc:description>This Thesis was approved for publication on 2025-04-16 at 07:41.</dc:description>
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          <dc:title>Hercules: A compiler for productive programming of heterogeneous systems</dc:title>
          <dc:creator>Arbore, Russel</dc:creator>
          <dc:date>2025-04-16</dc:date>
          <dc:contributor>Adve, Vikram</dc:contributor>
          <dc:subject>compilers</dc:subject>
          <dc:subject>heterogeneous systems</dc:subject>
          <dc:language>eng</dc:language>
          <dc:description>Modern computing systems increasingly rely on composing heterogeneous devices to improve performance and efficiency. Programming these systems is often unproductive: algorithm implementations must be coupled to system-specific logic, including device-specific optimizations, partitioning, and inter-device communication and synchronization, which requires developing different programs for different system configurations. We propose the Juno language, which represents general purpose applications in an imperative form that can be transformed into parallel, optimized, system-specific code using an expressive and granular imperative scheduling language. We also introduce the Hercules compiler, which uses a novel intermediate representation to represent general and device-specific parallel code in a manner that is easy to analyze and manipulate using schedules. Our system achieves competitive performance with hand-optimized device-specific code (geomean speedups of 1.25x and 1.48x on the CPU and GPU) and significantly outperforms a prior general purpose heterogeneous programming system (geomean speedups of 9.31x and 16.18x on the CPU and GPU).</dc:description>
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          <dc:identifier>https://hdl.handle.net/2142/129206</dc:identifier>
          <dc:rights>Copyright 2025 Russel Arbore</dc:rights>
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            <department>Siebel School Comp &amp; Data Sci</department>
            <discipline>Computer Science</discipline>
            <grantor>University of Illinois Urbana-Champaign</grantor>
            <name>M.S.</name>
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