A compiler approach to scalable concurrent program design

The programmer's most powerful tool for controlling complexity in program design is abstraction. We seek to use abstraction in the design of concurrent programs, so as to separate design decisions concerned with decomposition, communication, synchronization, mapping, granularity, and load balancing. This paper describes programming and compiler techniques intended to facilitate this design strategy. The programming techniques are based on a core programming notation with two important properties: the ability to separate concurrent programming concerns, and extensibility with reusable programmer-defined abstractions. The compiler techniques are based on a simple transformation system together with a set of compilation transformations and portable run-time support. The transformation system allows programmer-defined abstractions to be defined as source-to-source transformations that convert abstractions into the core notation. The same transformation system is used to apply compilation transformations that incrementally transform the core notation toward an abstract concurrent machine. This machine can be implemented on a variety of concurrent architectures using simple run-time support. The transformation, compilation, and run-time system techniques have been implemented and are incorporated in a public-domain program development toolkit. This toolkit operates on a wide variety of networked workstations, multicomputers, and shared-memory multiprocessors. It includes a program transformer, concurrent compiler, syntax checker, debugger, performance analyzer, and execution animator. A variety of substantial applications have been developed using the toolkit, in areas such as climate modeling and fluid dynamics

Density-Based Semantics for Reactive Probabilistic Programming

Synchronous languages are now a standard industry tool for critical embedded systems. Designers write high-level specifications by composing streams of values using block diagrams. These languages have been extended with Bayesian reasoning to program state-space models which compute a stream of distributions given a stream of observations. However, the semantics of probabilistic models is only defined for scheduled equations -- a significant limitation compared to dataflow synchronous languages and block diagrams which do not require any ordering. In this paper we propose two schedule agnostic semantics for a probabilistic synchronous language. The key idea is to interpret probabilistic expressions as a stream of un-normalized density functions which maps random variable values to a result and positive score. The co-iterative semantics interprets programs as state machines and equations are computed using a fixpoint operator. The relational semantics directly manipulates streams and is thus a better fit to reason about program equivalence. We use the relational semantics to prove the correctness of a program transformation required to run an optimized inference algorithm for state-space models with constant parameters

Hardware Synthesis from a Recursive Functional Language

Abstraction in hardware description languages stalled at the register-transfer level decades ago, yet few alternatives have had much success, in part because they provide only modest gains in expressivity. We propose to make a much larger jump: a compiler that synthesizes hardware from behavioral functional specifications. Our compiler translates general Haskell programs into a restricted intermediate representation before applying a series of semantics-preserving transformations, concluding with a simple syntax-directed translation to SystemVerilog. Here, we present the overall framework for this compiler, focusing on the IRs involved and our method for translating general recursive functions into equivalent hardware. We conclude with experimental results that depict the performance and resource usage of the circuitry generated with our compiler

Syntactical and Semantical Aspects of Faust

International audienceThis paper presents some syntactical and semantical aspects of FAUST (Functional AUdio STreams), a programming language for real-time sound processing and synthesis. The programming model of FAUST combines two approaches : functional programming and block-diagrams composition. It is based on a block-diagram algebra. It has a well defined formal semantic and can be compiled into efficient C/C++ code

On the Efficiency of Optimising Shallow Backtracking in Prolog

The cost of backtracking has been identified as one of the bottlenecks in achieving peak performance in compiled Prolog programs. Much of the backtracking in Prolog programs is shallow, i.e. is caused by unification failures in the head of a clause when there are more alternatives for the same procedure, and so special treatment of this form of backtracking has been proposed as a significant optimisation. This paper describes a modified WAM which optimises shallow backtracking. Four different implementation approaches are compared. A number of benchmark results are presented, measuring the relative tradeoffs between compilation time, code size, and run time. The results show that the speedup gained by this optimisation can be significant

XQuery Streaming by Forest Transducers

Streaming of XML transformations is a challenging task and only very few systems support streaming. Research approaches generally define custom fragments of XQuery and XPath that are amenable to streaming, and then design custom algorithms for each fragment. These languages have several shortcomings. Here we take a more principles approach to the problem of streaming XQuery-based transformations. We start with an elegant transducer model for which many static analysis problems are well-understood: the Macro Forest Transducer (MFT). We show that a large fragment of XQuery can be translated into MFTs --- indeed, a fragment of XQuery, that can express important features that are missing from other XQuery stream engines, such as GCX: our fragment of XQuery supports XPath predicates and let-statements. We then rely on a streaming execution engine for MFTs, one which uses a well-founded set of optimizations from functional programming, such as strictness analysis and deforestation. Our prototype achieves time and memory efficiency comparable to the fastest known engine for XQuery streaming, GCX. This is surprising because our engine relies on the OCaml built in garbage collector and does not use any specialized buffer management, while GCX's efficiency is due to clever and explicit buffer management.Comment: Full version of the paper in the Proceedings of the 30th IEEE International Conference on Data Engineering (ICDE 2014

Formally Specifying and Proving Operational Aspects of Forensic Lucid in Isabelle

A Forensic Lucid intensional programming language has been proposed for intensional cyberforensic analysis. In large part, the language is based on various predecessor and codecessor Lucid dialects bound by the higher-order intensional logic (HOIL) that is behind them. This work formally specifies the operational aspects of the Forensic Lucid language and compiles a theory of its constructs using Isabelle, a proof assistant system.Comment: 23 pages, 3 listings, 3 figures, 1 table, 1 Appendix with theorems, pp. 76--98. TPHOLs 2008 Emerging Trends Proceedings, August 18-21, Montreal, Canada. Editors: Otmane Ait Mohamed and Cesar Munoz and Sofiene Tahar. The individual paper's PDF is at http://users.encs.concordia.ca/~tphols08/TPHOLs2008/ET/76-98.pd