Tatlock, ZacharyCeze, LuisSmith, Gus Henry2024-10-162024-10-162024-10-162024Smith_washington_0250E_27452.pdfhttps://hdl.handle.net/1773/52457Thesis (Ph.D.)--University of Washington, 2024Compilers convert between representations—usually, from higher-level, human writable code to lower-level, machine-readable code. A compiler backend is the portion of the compiler containing optimizations and code generation routines for a specific hardware target. In this dissertation, I advocate for a specific way of building compiler backends: namely, by automatically generating them from explicit, formal models of hardware using automated reasoning algorithms. I describe how automatically generating compilers from formal models of hardware leads to increased optimization ability, stronger correctness guarantees, and reduced development time for compiler backends. As evidence, I present two case studies: first, Glenside, which uses equality saturation to increase the 3LA compiler’s ability to offload operations to machine learning accelerators, and second, Lakeroad, a technology mapper for FPGAs which uses program synthesis and semanticsextracted from Verilog to map hardware designs to complex, programmable hardware primitives.application/pdfen-USCC BYautomated reasoningcompilersequality saturationhardware designprogram synthesisprogram synthesisComputer scienceComputer engineeringComputer science and engineeringThesis