A compiler extension for parallelizing arrays automatically on the cell heterogeneous processor

This paper describes the approaches taken to extend an array programming language compiler using a Virtual SIMD Machine (VSM) model for parallelizing array operations on Cell Broadband Engine heterogeneous machine. This development is part of ongoing work at the University of Glasgow for developing array compilers that are beneficial for applications in many areas such as graphics, multimedia, image processing and scientific computation. Our extended compiler, which is built upon the VSM interface, eases the parallelization processes by allowing automatic parallelisation without the need for any annotations or process directives. The preliminary results demonstrate significant improvement especially on data-intensive applications

Liveness-Driven Random Program Generation

Randomly generated programs are popular for testing compilers and program analysis tools, with hundreds of bugs in real-world C compilers found by random testing. However, existing random program generators may generate large amounts of dead code (computations whose result is never used). This leaves relatively little code to exercise a target compiler's more complex optimizations. To address this shortcoming, we introduce liveness-driven random program generation. In this approach the random program is constructed bottom-up, guided by a simultaneous structural data-flow analysis to ensure that the generator never generates dead code. The algorithm is implemented as a plugin for the Frama-C framework. We evaluate it in comparison to Csmith, the standard random C program generator. Our tool generates programs that compile to more machine code with a more complex instruction mix.Comment: Pre-proceedings paper presented at the 27th International Symposium on Logic-Based Program Synthesis and Transformation (LOPSTR 2017), Namur, Belgium, 10-12 October 2017 (arXiv:1708.07854

Linguistic Reflection in Java

Reflective systems allow their own structures to be altered from within. Here we are concerned with a style of reflection, called linguistic reflection, which is the ability of a running program to generate new program fragments and to integrate these into its own execution. In particular we describe how this kind of reflection may be provided in the compiler-based, strongly typed object-oriented programming language Java. The advantages of the programming technique include attaining high levels of genericity and accommodating system evolution. These advantages are illustrated by an example taken from persistent programming which shows how linguistic reflection allows functionality (program code) to be generated on demand (Just-In-Time) from a generic specification and integrated into the evolving running program. The technique is evaluated against alternative implementation approaches with respect to efficiency, safety and ease of use.Comment: 25 pages. Source code for examples at http://www-ppg.dcs.st-and.ac.uk/Java/ReflectionExample/ Dynamic compilation package at http://www-ppg.dcs.st-and.ac.uk/Java/DynamicCompilation

A Genetic Programming Problem Definition Language Code Generator for the EpochX Framework

There are many different genetic programming (GP) frameworks that can be used to implement algorithms to solve a particular optimization problem. In order to use a framework, users need to become familiar with a large numbers of source code before actually implementing the algorithm, adding a learning overhead. In some cases, this can prevent users from trying out different frameworks. This paper discusses the implementation of a code generator in the EpochX framework to facilitate the implementation of GP algorithms. The code generator is based on the GP defini- tion language (GPDL), which is a framework-independent language that can be used to specify GP problems

Introducing Molly: Distributed Memory Parallelization with LLVM

Programming for distributed memory machines has always been a tedious task, but necessary because compilers have not been sufficiently able to optimize for such machines themselves. Molly is an extension to the LLVM compiler toolchain that is able to distribute and reorganize workload and data if the program is organized in statically determined loop control-flows. These are represented as polyhedral integer-point sets that allow program transformations applied on them. Memory distribution and layout can be declared by the programmer as needed and the necessary asynchronous MPI communication is generated automatically. The primary motivation is to run Lattice QCD simulations on IBM Blue Gene/Q supercomputers, but since the implementation is not yet completed, this paper shows the capabilities on Conway's Game of Life