HackerPapers

arXiv:2505.22610cs.PL

TPDE: A Fast Adaptable Compiler Back-End Framework

Tobias Schwarz, Tobias Kamm, Alexis Engelke

Early discovery. Linked by one identifiable commenter. This paper is outside the main ranking; a mention is not an endorsement.

Abstract

Fast machine code generation is especially important for fast start-up just-in-time compilation, where the compilation time is part of the end-to-end latency. However, widely used compiler frameworks like LLVM do not prioritize fast compilation and require an extra IR translation step increasing latency even further; and rolling a custom code generator is a substantial engineering effort, especially when targeting multiple architectures. Therefore, in this paper, we present TPDE, a compiler back-end framework that adapts to existing code representations in SSA form. Using an IR-specific adapter providing canonical access to IR data structures and a specification of the IR semantics, the framework performs one analysis pass and then performs the compilation in just a single pass, combining instruction selection, register allocation, and instruction encoding. The generated target instructions are primarily derived code written in high-level language through LLVM's Machine IR, easing portability to different architectures while enabling optimizations during code generation. To show the generality of our framework, we build a new back-end for LLVM from scratch targeting x86-64 and AArch64. Performance results on SPECint 2017 show that we can compile LLVM-IR 8--24x faster than LLVM -O0 while being on-par in terms of run-time performance. We also demonstrate the benefits of adapting to domain-specific IRs in JIT contexts, particularly WebAssembly and database query compilation, where avoiding the extra IR translation further reduces compilation latency.

arXiv comments
23 pages, 10 figures
Journal reference
DOI
Subjects
cs.PLProgramming Languages

On Hacker News

Linked by 1 identifiable commenter in 1 comment across 1 thread, from Sep 2025 to Sep 2025. Found in 3 HN submissions from May 2025 to Jun 2025. Open submission discussions.

Comments linking this paper, per year.

Discussed in comments1 thread

Submitted to Hacker News

Connected through shared HN threads, not inferred similarity or a recommendation.