Abstract
Automation is useful to facilitate reverse code generation from normal code. Here, we describe our source-to-source compilation approaches to automatic reverse code generation, developed along three different translation tools/frameworks. At RPI, we are developing frameworks based on PIPS, which is a purely source-to-source translation and optimization tool for parallel computing, and on CLANG/LLVM, which is a full compiler complete with backend processing and optimizers. At ORNL we are continuing development of the seminal reverse computation framework called RCC (Reverse C Compiler) system. For all three systems, we present some implementation issues and challenges encountered in our development.
Kalyan Perumalla
As a Federal Program Manager in Advanced Scientific Computing Research at the U.S. Dept. of Energy, Office of Science, Kalyan Perumalla manages a $100-million R&D portfolio covering AI, HPC, Quantum, SciDAC, and Basic Computer Science. In his 25-year R&D leadership experience, he previously led advanced R&D as Distinguished Research Staff Member at the Oak Ridge National Laboratory (ORNL) developing scalable software and applications on the world’s largest supercomputers for 17 years, including as a line manager and a founding group leader. He has held senior faculty and adjunct appointments at UTK, GT, and UNL, and was an IAS Fellow at Durham University.