Interprocedural Data Flow Based Optimizations for Distributed Memory Compilation

Interprocedural Data Flow Based Optimizations for Distributed Memory Compilation

Data parallel languages like High Performance Fortran (HPF) are emerging as the architecture independent mode of programming distributed memory parallel machines. In this paper, we present the interprocedural optimizations required for compiling applications having irregular data access patterns, when coded in such data parallel languages. We have developed an Interprocedural Partial Redundancy...

Interprocedural Partial Redundancy Elimination With Application to Distributed Memory Compilation

Memory Optimizations for Distributed Stream-based Applications

Verifying Data Flow Optimizations forJust-in-Time Compilation

Annotations are often added to mobile code to reduce the optimization burden of just-intime compilers. However, these annotations are not checked for correctness and must be trusted—incorrect or malicious annotations could lead to the generation of incorrect or insecure code. We present a timeand space efficient method for verifying the results of the large class of data flow optimizations. Thi...

Interprocedural data flow decompilation

Traditional compiler data ow analysis techniques are used to transform the intermediate representation of a decompiled program to a higher representation that eliminates low-level concepts such as registers and condition codes, and reintroduces the high-level concept of expression. Summary data ow information is collected on condition codes and registers, and is propagated across basic blocks a...