A Functional Approach to Hardware Software Co-Design

Developing software for embedded systems presents quite the challenge---not only do these systems demand good knowledge of the hardware they run on, but their limited resources also make it difficult to achieve efficiency. For embedded systems with different kinds of processing elements, the challenge is even greater; the presence of heterogeneous elements both raises all of the issues associated with homogeneous systems, and may also cause non-uniform system development and capability.In this thesis we explore a functional approach to heterogeneous system development, with a staged hardware software co-design language embedded in Haskell, to address many of the modularity problems typically found in such systems. This staged approach enables designers to build their applications from reusable components and skeletons, while retaining control over much of the generated source code. Design exploration also benefits from the functional approach, since Haskell\u27s type classes can be used to ensure that certain operations will be available. As a result, a developer can not only write for hardware and software in the co-design language, but she can also write generic programs that are suitable for both.Internally, the co-design language is based on a monadic representation of imperative programs that abstracts away from its underlying statement, expression, and predicate types by establishing an interface to their respective interpreters. Programs are thus loosely coupled to their underlying types, giving a clear separation of concerns. The compilation process is expressed as a series of translations between progressively smaller typed languages, which safeguards against many common errors.In addition to the hardware software co-design language, this thesis also introduces a language for expressing digital signal processing algorithms, using a model of synchronous data-flow that is embedded in Haskell. The language supports definitions in a functional style, reducing the gap between an algorithm\u27s mathematical specification and its implementation. A vector language is also presented, which builds on a functional representation that guarantees fusion for arrays. Both of these languages are intended to be extensions of the co-design language, but neither one is dependent on it and can thus be used to extend other languages as well

A functional approach to heterogeneous computing in embedded systems

Developing programs for embedded systems presents quite a challenge; not only should programs be resource efficient, as they operate under memory and timing constraints, but they should also take full advantage of the hardware to achieve maximum performance. Since performance is such a significant factor in the design of embedded systems, modern systems typically incorporate more than one kind of processing element to benefit from specialized processing capabilities. For such heterogeneous systems the challenge in developing programs is even greater.In this thesis we explore a functional approach to heterogeneous system development as a means to address many of the modularity problems that are typically found in the application of low-level imperative programming for embedded systems. In particular, we explore a staged hardware software co-design language that we name Co-Feldspar and embed in Haskell. The staged approach enables designers to build their applications from reusable components and skeletons while retaining control over much of the generated source code. Furthermore, by embedding the language in Haskell we can exploit its type classes to write not only hardware and software programs, but also generic programs with overloaded instructions and expressions. We demonstrate the usefulness of the functional approach for co-design on a cryptographic example and signal processing filters, and benchmark software and mixed hardware-software implementations. Co-Feldspar currently adopts a monadic interface, which provides an imperative functional programming style that is suitable for explicit memory management and algorithms that rely on a certain evaluation order. For algorithms that are better defined as pure functions operating on immutable values, we provide a signal and array library that extends a monadic language, like Co-Feldspar. These extensions permit a functional style of programming by composing high-level combinators. Our compiler transforms such high-level code into efficient programs with mutating code. In particular, we show how to execute an FFT safely in-place, and how to describe a FIR and IIR filter efficiently as streams. Co-Feldspar’s monadic interface is however quite invasive; not only is the burden of explicit memory management quite heavy on the user, it is also quite easy to shoot on eself in the foot. It is for these reasons that we also explore a dynamic memory management discipline that is based on regions but predictable enough to be of use for embedded systems. Specifically, this thesis introduces a program analysis which annotates values with dynamically allocated memory regions. By limiting our efforts to functional languages that target embedded software, we manage to define a region inference algorithm that is considerably simpler than traditional approaches

A Lazy Approach for Supporting Nested Transactions

Transactional memory (TM) is a compelling alternative to traditional synchronization, and implementing TM primitives directly in hardware offers a potential performance advantage over software-based methods. In this paper, we demonstrate that many of the actions associated with transaction abort and commit may be performed lazily -- that is, incrementally, and on demand. This technique is ideal for hardware, since it requires little space or work; in addition, it can improve performance by sparing accesses to committing or aborting locations from having to stall until the commit or abort completes. We further show that our lazy abort and commit technique supports open nesting and orElse, two language-level proposals which rely on transactional nesting. We also provide design notes for supporting lazy abort and commit on our own hardware TM system, based on VTM

Fine-grained visualization pipelines and lazy functional languages

The pipeline model in visualization has evolved from a conceptual model of data processing into a widely used architecture for implementing visualization systems. In the process, a number of capabilities have been introduced, including streaming of data in chunks, distributed pipelines, and demand-driven processing. Visualization systems have invariably built on stateful programming technologies, and these capabilities have had to be implemented explicitly within the lower layers of a complex hierarchy of services. The good news for developers is that applications built on top of this hierarchy can access these capabilities without concern for how they are implemented. The bad news is that by freezing capabilities into low-level services expressive power and flexibility is lost. In this paper we express visualization systems in a programming language that more naturally supports this kind of processing model. Lazy functional languages support fine-grained demand-driven processing, a natural form of streaming, and pipeline-like function composition for assembling applications. The technology thus appears well suited to visualization applications. Using surface extraction algorithms as illustrative examples, and the lazy functional language Haskell, we argue the benefits of clear and concise expression combined with fine-grained, demand-driven computation. Just as visualization provides insight into data, functional abstraction provides new insight into visualization

RELEASE: A High-level Paradigm for Reliable Large-scale Server Software

Erlang is a functional language with a much-emulated model for building reliable distributed systems. This paper outlines the RELEASE project, and describes the progress in the rst six months. The project aim is to scale the Erlang's radical concurrency-oriented programming paradigm to build reliable general-purpose software, such as server-based systems, on massively parallel machines. Currently Erlang has inherently scalable computation and reliability models, but in practice scalability is constrained by aspects of the language and virtual machine. We are working at three levels to address these challenges: evolving the Erlang virtual machine so that it can work effectively on large scale multicore systems; evolving the language to Scalable Distributed (SD) Erlang; developing a scalable Erlang infrastructure to integrate multiple, heterogeneous clusters. We are also developing state of the art tools that allow programmers to understand the behaviour of massively parallel SD Erlang programs. We will demonstrate the e ectiveness of the RELEASE approach using demonstrators and two large case studies on a Blue Gene

Dynamically typed languages

Dynamically typed languages such as Python and Ruby have experienced a rapid grown in popularity in recent times. However, there is much confusion as to what makes these languages interesting relative to statically typed languages, and little knowledge of their rich history. In this chapter I explore the general topic of dynamically typed languages, how they differ from statically typed languages, their history, and their defining features