Late-bound code generation

Each time a function or method is invoked during the execution of a program, a stream of instructions is issued to some underlying hardware platform. But exactly what underlying hardware, and which instructions, is usually left implicit. However in certain situations it becomes important to control these decisions. For example, particular problems can only be solved in real-time when scheduled on specialised accelerators, such as graphics coprocessors or computing clusters. We introduce a novel operator for hygienically reifying the behaviour of a runtime function instance as a syntactic fragment, in a language which may in general differ from the source function definition. Translation and optimisation are performed by recursively invoked, dynamically dispatched code generators. Side-effecting operations are permitted, and their ordering is preserved. We compare our operator with other techniques for pragmatic control, observing that: the use of our operator supports lifting arbitrary mutable objects, and neither requires rewriting sections of the source program in a multi-level language, nor interferes with the interface to individual software components. Due to its lack of interference at the abstraction level at which software is composed, we believe that our approach poses a significantly lower barrier to practical adoption than current methods. The practical efficacy of our operator is demonstrated by using it to offload the user interface rendering of a smartphone application to an FPGA coprocessor, including both statically and procedurally defined user interface components. The generated pipeline is an application-specific, statically scheduled processor-per-primitive rendering pipeline, suitable for place-and-route style optimisation. To demonstrate the compatibility of our operator with existing languages, we show how it may be defined within the Python programming language. We introduce a transformation for weakening mutable to immutable named bindings, termed let-weakening, to solve the problem of propagating information pertaining to named variables between modular code generating units.Open Acces

Open Programming Language Interpreters

Context: This paper presents the concept of open programming language interpreters and the implementation of a framework-level metaobject protocol (MOP) to support them. Inquiry: We address the problem of dynamic interpreter adaptation to tailor the interpreter's behavior on the task to be solved and to introduce new features to fulfill unforeseen requirements. Many languages provide a MOP that to some degree supports reflection. However, MOPs are typically language-specific, their reflective functionality is often restricted, and the adaptation and application logic are often mixed which hardens the understanding and maintenance of the source code. Our system overcomes these limitations. Approach: We designed and implemented a system to support open programming language interpreters. The prototype implementation is integrated in the Neverlang framework. The system exposes the structure, behavior and the runtime state of any Neverlang-based interpreter with the ability to modify it. Knowledge: Our system provides a complete control over interpreter's structure, behavior and its runtime state. The approach is applicable to every Neverlang-based interpreter. Adaptation code can potentially be reused across different language implementations. Grounding: Having a prototype implementation we focused on feasibility evaluation. The paper shows that our approach well addresses problems commonly found in the research literature. We have a demonstrative video and examples that illustrate our approach on dynamic software adaptation, aspect-oriented programming, debugging and context-aware interpreters. Importance: To our knowledge, our paper presents the first reflective approach targeting a general framework for language development. Our system provides full reflective support for free to any Neverlang-based interpreter. We are not aware of any prior application of open implementations to programming language interpreters in the sense defined in this paper. Rather than substituting other approaches, we believe our system can be used as a complementary technique in situations where other approaches present serious limitations

Static Computation and Reflection

Thesis (PhD) - Indiana University, Computer Sciences, 2008Most programming languages do not allow programs to inspect their static type information or perform computations on it. C++, however, lets programmers write template metaprograms, which enable programs to encode static information, perform compile-time computations, and make static decisions about run-time behavior. Many C++ libraries and applications use template metaprogramming to build specialized abstraction mechanisms, implement domain-specific safety checks, and improve run-time performance. Template metaprogramming is an emergent capability of the C++ type system, and the C++ language specification is informal and imprecise. As a result, template metaprogramming often involves heroic programming feats and often leads to code that is difficult to read and maintain. Furthermore, many template-based code generation and optimization techniques rely on particular compiler implementations, rather than language semantics, for performance gains. Motivated by the capabilities and techniques of C++ template metaprogramming, this thesis documents some common programming patterns, including static computation, type analysis, generative programming, and the encoding of domain-specific static checks. It also documents notable shortcomings to current practice, including limited support for reflection, semantic ambiguity, and other issues that arise from the pioneering nature of template metaprogramming. Finally, this thesis presents the design of a foundational programming language, motivated by the analysis of template metaprogramming, that allows programs to statically inspect type information, perform computations, and generate code. The language is specified as a core calculus and its capabilities are presented in an idealized setting

System Synthesis from a Monadic Functional Language

Embedded systems typically combine a mixture of heterogeneous components, some that are software executing on general purpose CPUs, some that are off-the-shelf hardware components, and some that are application specific circuitry. A major challenge when designing and implementing such systems is the dissimilar models of computation exhibited by hardware and software targets. To successfully navigate this challenge, components must be implemented in a way that does not unnecessarily bias the implementation towards either computational model, allowing the components to be retargeted as application requirements change. This dissertation presents an approach to this problem using a functional programming language extended with monadic imperative and concurrency effects. We argue that these language features allow components to be implemented and compiled to either hardware or software targets. To demonstrate this claim, we detail the design of such a language, Oread. Moreover, we describe the compilation of Oread to both hardware, via VHDL, and software, via C. Using these compilation techniques, we describe the development of a digital processing component in Oread and the integration of that component into a larger system

Toatie : functional hardware description with dependent types

Describing correct circuits remains a tall order, despite four decades of evolution in Hardware Description Languages (HDLs). Many enticing circuit architectures require recursive structures or complex compile-time computation — two patterns that prove difficult to capture in traditional HDLs. In a signal processing context, the Fast FIR Algorithm (FFA) structure for efficient parallel filtering proves to be naturally recursive, and most Multiple Constant Multiplication (MCM) blocks decompose multiplications into graphs of simple shifts and adds using demanding compile time computation. Generalised versions of both remain mostly in academic folklore. The implementations which do exist are often ad hoc circuit generators, written in software languages. These pose challenges for verification and are resistant to composition. Embedded functional HDLs, that represent circuits as data, allow for these descriptions at the cost of forcing the designer to work at the gate-level. A promising alternative is to use a stand-alone compiler, representing circuits as plain functions, exemplified by the CλaSH HDL. This, however, raises new challenges in capturing a circuit’s staging — which expressions in the single language should be reduced during compile-time elaboration, and which should remain in the circuit’s run-time? To better reflect the physical separation between circuit phases, this work proposes a new functional HDL (representing circuits as functions) with first-class staging constructs. Orthogonal to this, there are also long-standing challenges in the verification of parameterised circuit families. Industry surveys have consistently reported that only a slim minority of FPGA projects reach production without non-trivial bugs. While a healthy growth in the adoption of automatic formal methods is also reported, the majority of testing remains dynamic — presenting difficulties for testing entire circuit families at once. This research offers an alternative verification methodology via the combination of dependent types and automatic synthesis of user-defined data types. Given precise enough types for synthesisable data, this environment can be used to develop circuit families with full functional verification in a correct-by-construction fashion. This approach allows for verification of entire circuit families (not just one concrete member) and side-steps the state-space explosion of model checking methods. Beyond the existing work, this research offers synthesis of combinatorial circuits — not just a software model of their behaviour. This additional step requires careful consideration of staging, erasure & irrelevance, deriving bit representations of user-defined data types, and a new synthesis scheme. This thesis contributes steps towards HDLs with sufficient expressivity for awkward, combinatorial signal processing structures, allowing for a correct-by-construction approach, and a prototype compiler for netlist synthesis.Describing correct circuits remains a tall order, despite four decades of evolution in Hardware Description Languages (HDLs). Many enticing circuit architectures require recursive structures or complex compile-time computation — two patterns that prove difficult to capture in traditional HDLs. In a signal processing context, the Fast FIR Algorithm (FFA) structure for efficient parallel filtering proves to be naturally recursive, and most Multiple Constant Multiplication (MCM) blocks decompose multiplications into graphs of simple shifts and adds using demanding compile time computation. Generalised versions of both remain mostly in academic folklore. The implementations which do exist are often ad hoc circuit generators, written in software languages. These pose challenges for verification and are resistant to composition. Embedded functional HDLs, that represent circuits as data, allow for these descriptions at the cost of forcing the designer to work at the gate-level. A promising alternative is to use a stand-alone compiler, representing circuits as plain functions, exemplified by the CλaSH HDL. This, however, raises new challenges in capturing a circuit’s staging — which expressions in the single language should be reduced during compile-time elaboration, and which should remain in the circuit’s run-time? To better reflect the physical separation between circuit phases, this work proposes a new functional HDL (representing circuits as functions) with first-class staging constructs. Orthogonal to this, there are also long-standing challenges in the verification of parameterised circuit families. Industry surveys have consistently reported that only a slim minority of FPGA projects reach production without non-trivial bugs. While a healthy growth in the adoption of automatic formal methods is also reported, the majority of testing remains dynamic — presenting difficulties for testing entire circuit families at once. This research offers an alternative verification methodology via the combination of dependent types and automatic synthesis of user-defined data types. Given precise enough types for synthesisable data, this environment can be used to develop circuit families with full functional verification in a correct-by-construction fashion. This approach allows for verification of entire circuit families (not just one concrete member) and side-steps the state-space explosion of model checking methods. Beyond the existing work, this research offers synthesis of combinatorial circuits — not just a software model of their behaviour. This additional step requires careful consideration of staging, erasure & irrelevance, deriving bit representations of user-defined data types, and a new synthesis scheme. This thesis contributes steps towards HDLs with sufficient expressivity for awkward, combinatorial signal processing structures, allowing for a correct-by-construction approach, and a prototype compiler for netlist synthesis

Structural abstraction: a mechanism for modular program construction

Abstraction mechanisms in programming languages aim to allow orthogonal pieces of functionality to be developed separately; complex software can then be constructed through the composition of these pieces. The effectiveness of such mechanisms lies in their support for modularity and reusability: The behavior of a piece of code should be reasoned about modularly---independently of the specific compositions it may participate in; the computation of a piece of code should allow specialization, so that it is reusable for different compositions. This dissertation introduces structural abstraction: a mechanism that advances the state of the art by allowing the writing of highly reusable code---code whose structure can be specialized per composition, while maintaining a high level of modularity. Structural abstraction provides a disciplined way for code to inspect the structure of its clients in composition, and declare its own structure accordingly. The hallmark feature of structural abstraction is that, despite its emphasis on greater reusability, it still allows modular type checking: A piece of structurally abstract code can be type-checked independently of its uses in compositions---an invaluable feature for highly reusable components that will be statically composed by other programmers. This dissertation introduces two structural abstraction techniques: static type conditions, and morphing. Static type conditions allow code to be conditionally declared based on subtyping constraints. A client of a piece of code can configure a desirable set of features by composing the code with types that satisfy the appropriate subtyping conditions. Morphing allows code to be iteratively declared, by statically reflecting over the structural members of code that it would be composed with. A morphing piece of code can mimic the structure of its clients in composition, or change its shape according to its clients in a pattern-based manner. Using either static type conditions or morphing, the structure of a piece of code is not statically determined, but can be automatically specialized by clients. Static type conditions and morphing both guarantee the modular type-safety of code: regardless of specific client configurations, code is guaranteed to be well-typed.Ph.D.Committee Chair: Yannis Smaragdakis; Committee Member: Oege de Moor; Committee Member: Richard LeBlanc; Committee Member: Santosh Pande; Committee Member: Spencer Rugabe

DYNAMIC LANGUAGE UPDATING

With respect to traditional systems, language interpreters are hard to evolve and the adoption of evolved languages is slow. Language evolution is hindered by the fact that their implementations often overlook design principles, especially those related to modularity. Consequently, language implementations and their updates are monolithic. Language evolution often breaks the backward compatibility and requires developers to rewrite their applications. Furthermore, there is little or no support to evolve language interpreters at runtime. This would be useful for systems that cannot be shut down and to support context-aware interpreters. To tackle these issues, we designed the concept of open interpreters which provide support for language evolution through reflection. Open interpreters allow one to partially update a language to maintain the backward compatibility. Furthermore, they allow one to dynamically update a language without stopping the overlying application. Open interpreters can be dynamically tailored on the task to be solved. The peculiarity of this approach is that the evolution code is completely separated from the application or the original interpreter code. In this dissertation we define the concept of open interpreters, we design a possible implementation model, we describe a prototype implantation and provide the proof-of-concept examples applied to various domains