Contextual dispatch for function specialization

In order to generate efficient code, dynamic language compilers often need information, such as dynamic types, not readily available in the program source. Leveraging a mixture of static and dynamic information, these compilers speculate on the missing information. Within one compilation unit, they specialize the generated code to the previously observed behaviors, betting that past is prologue. When speculation fails, the execution must jump back to unoptimized code. In this paper, we propose an approach to further the specialization, by disentangling classes of behaviors into separate optimization units. With contextual dispatch, functions are versioned and each version is compiled under different assumptions. When a function is invoked, the implementation dispatches to a version optimized under assumptions matching the dynamic context of the call. As a proof-of-concept, we describe a compiler for the R language which uses this approach. We evaluate contextual dispatch on a set of benchmarks and compare it to traditional speculation with deoptimization techniques. Our implementation is, on average, 1.7× faster than the GNU R reference implementation, and contextual dispatch improves the performance of 18 out of 46 programs in our benchmark suite. CCS Concepts: • Software and its engineering → Compilers.