Machine-specific optimization methods for C/C++ applications that are distributed in the LLVM intermediate representation format

Abstract

This paper analyzes approaches for optimizing C/C++ applications used in twostage compilation system, allowing distributing such applications in the LLVM (low level virtual machine) intermediate representation. The on-stack replacement technique implemented in the LLVM just-in-time compiler is described. The paper presents a static instrumentation technique with incomplete control flow edge covering and its correction to the full control flow profile. The proposed approach allows the derived profile information to be comparable in quality to the classical approach while significantly reducing the profiling overhead. 

Also, the technique for converting dynamically collected profile to LLVM profile format for statically compiled applications is presented. This paper evaluates both existing optimizations modified for using the collected profile and the newly developed ones. Implemented profile based inlining, outlining, speculative devirtualization. Also implemented annotation of control flow graph by profile weights to make profile based optimizations easy for debugging. Proposed the technique which allows using the prefetch instructions to improve the effectiveness of array processing codes. This paper describes the approach for building a specific cloud application storage that allows solving program optimization and protection problems. Finally, we present the approach for reducing compilation and optimization overhead in the cloud infrastructure.