CPS Transformation of Beta-Redexes

The extra compaction of Sabry and Felleisen's transformation is due to making continuations occur first in CPS terms and classifying more redexes as administrative. We show that the extra compaction is actually independent of the relative positions of values and continuations and furthermore that it is solely due to a context-sensitive transformation of beta-redexes. We stage the more compact CPS transformation into a first-order uncurrying phase and a context-insensitive CPS transformation. We also dene a context-insensitive CPS transformation that is just as compact. This CPS transformation operates in one pass and is dependently typed.Keywords: Continuation-passing style (CPS), Plotkin, Fischer, one-pass CPStransformation, two-level lambda-calculus, generalized reduction

CPS Transformation of Beta-Redexes

The extra compaction of the most compacting CPS transformation in existence, which is due to Sabry and Felleisen, is generally attributed to (1) making continuations occur first in CPS terms and (2) classifying more redexes as administrative. We show that this extra compaction is actually independent of the relative positions of values and continuations and furthermore that it is solely due to a context-sensitive transformation of beta-redexes. We stage the more compact CPS transformation into a first-order uncurrying phase and a context-insensitive CPS transformation. We also define a context-insensitive CPS transformation that provides the extra compaction. This CPS transformation operates in one pass and is dependently typed

On One-Pass CPS Transformations

We bridge two distinct approaches to one-pass CPS transformations, i.e., CPS transformations that reduce administrative redexes at transformation time instead of in a post-processing phase. One approach is compositional and higher-order, and is due to Appel, Danvy and Filinski, and Wand, building on Plotkin's seminal work. The other is non-compositional and based on a syntactic theory of the lambda-calculus, and is due to Sabry and Felleisen. To relate the two approaches, we use Church encoding, Reynolds's defunctionalization, and an implementation technique for syntactic theories, refocusing, developed in the second author's PhD thesis

On One-Pass CPS Transformations

We bridge two distinct approaches to one-pass CPS transformations, i.e., CPS transformations that reduce administrative redexes at transformation time instead of in a post-processing phase. One approach is compositional and higher-order, and is independently due to Appel, Danvy and Filinski, and Wand, building on Plotkin's seminal work. The other is non-compositional and based on a reduction semantics for the lambda-calculus, and is due to Sabry and Felleisen. To relate the two approaches, we use three tools: Reynolds's defunctionalization and its left inverse, refunctionalization; a special case of fold-unfold fusion due to Ohori and Sasano, fixed-point promotion; and an implementation technique for reduction semantics due to Danvy and Nielsen, refocusing. This work is directly applicable to transforming programs into monadic normal form

On the Static and Dynamic Extents of Delimited Continuations

We show that breadth-first traversal exploits the difference between the static delimited-control operator shift (alias S) and the dynamic delimited-control operator control (alias F). For the last 15 years, this difference has been repeatedly mentioned in the literature but it has only been illustrated with one-line toy examples. Breadth-first traversal fills this vacuum. We also point out where static delimited continuations naturally give rise to the notion of control stack whereas dynamic delimited continuations can be made to account for a notion of `control queue.'

Optimal program variant generation for hybrid manycore systems

Field Programmable Gate Arrays promise to deliver superior energy efficiency in heterogeneous high performance computing, as compared to multicore CPUs and GPUs. The rate of adoption is however hampered by the relative difficulty of programming FPGAs. High-level synthesis tools such as Xilinx Vivado, Altera OpenCL or Intel's HLS address a large part of the programmability issue by synthesizing a Hardware Description Languages representation from a high-level specification of the application, given in programming languages such as OpenCL C, typically used to program CPUs and GPUs. Although HLS solutions make programming easier, they fail to also lighten the burden of optimization. Application developers must rely on expert knowledge to manually optimize their applications for each target device, meaning that traditional HLS solutions do not offer a solution to the issue of performance portability. This state of fact prompted the development of compiler frameworks such as TyTra that operate at an even higher level of abstraction that is amenable to the use of Design Space Exploration (DSE). With DSE the initial program specification can be seen as the starting location in a search-space of correct-by-construction program transformations. In TyTra the search-space is generated from the transitive-closure of term-level transformations derived from type-level transformations. Compiler frameworks such as TyTra theoretically solve the issue of performance portability by providing a way to automatically generate alternative correct program variants. They however suffer from the very practical issue that the generated space is often too large to fully explore. As a consequence, the globally optimal solution may be overlooked. In this work we provide a novel solution to issue performance portability by deriving an efficient yet effective DSE strategy for the TyTra compiler framework. We make use of categorical data types to derive categorical semantics for the formal languages that describe the terms, types, cost-performance estimates and their transformations. From these we define a category of interpretations for TyTra applications, from which we derive a DSE strategy that finds the globally optimal transformation sequence in polynomial time. This is achieved by reducing the size of the generated search space. We formally state and prove a theorem for this claim and then show that the polynomial run-time for our DSE strategy has practically negligible coefficients leading to sub-second exploration times for realistic applications

Dynamic Compilation for Functional Programs

Diese Arbeit behandelt die dynamische, zur Laufzeit stattfindende Übersetzung und Optimierung funktionaler Programme. Ziel der Optimierung ist die erhöhte Laufzeiteffizient der Programme, die durch die compilergesteuerte Eliminierung von Abstraktionen der Programmiersprache erreicht wird. Bei der Implementierung objekt-orientierter Programmiersprachen werden bereits seit mehreren Jahrzehnten Compiler-Techniken zur Laufzeit eingesetzt, um objekt-orientierte Programme effizient ausführen zu können. Spätestens seit der Einführung der Programmiersprache Java und ihres auf einer abstrakten Maschine basierenden Ausführungsmodells hat sich die Praktikabilität dieser Implementierungstechnik gezeigt. Viele Eigenschaften moderner Programmiersprachen konnten erst durch den Einsatz dynamischer Transformationstechniken effizient realisiert werden, wie zum Beispiel das dynamische Nachladen von Programmteilen (auch über Netzwerke), Reflection sowie verschiedene Sicherheitslösungen (z.B. Sandboxing). Ziel dieser Arbeit ist zu zeigen, dass rein funktionale Programmiersprachen auf ähnliche Weise effizient implementiert werden können, und sogar Vorteile gegenüber den allgemein eingesetzten objekt-orientierten Sprachen bieten, was die Effizienz, Sicherheit und Korrektheit von Programmen angeht. Um dieses Ziel zu erreichen, werden in dieser Arbeit Implementierungstechniken entworfen bzw. aus bestehenden Lösungen weiterentwickelt, welche die dynamische Kompilierung und Optimierung funktionaler Programme erlauben: zum einen präsentieren wir eine Programmzwischendarstellung (getypte dynamische Continuation-Passing-Style-Darstellung), welche sich zur dynamischen Kompilierung und Optimierung eignet. Basierend auf dieser Darstellung haben wir eine Erweiterung zur verzögerten und selektiven Codeerzeugung von Programmteilen entwickelt. Der wichtigste Beitrag dieser Arbeit ist die dynamische Spezialisierung zur Eliminierung polymorpher Funktionen und Datenstrukturen, welche die Effizienz funktionaler Programme deutlich steigern kann. Die präsentierten Ergebnisse experimenteller Messungen eines prototypischen Ausführungssystems belegen, dass funktionale Programme effizient dynamisch kompiliert werden können.This thesis is about dynamic translation and optimization of functional programs. The goal of the optimization is increased run-time efficiency, which is obtained by compiler-directed elimination of programming language abstractions. Object-oriented programming languages have been implemented for several decades using run-time compilation techniques. With the introduction of the Java programming language and its virtual machine-based execution model, the practicability of this implementation method for real-world applications has been proved. Many aspects of modern programming languages, such as dynamic loading and linking of code (even across networks), reflection and security solutions (e.g., sandboxing) can be realized efficiently only by using dynamic transformation techniques. The goal of this work is to show that functional programming languages can be efficiently implemented in a similar way, and that these languages even offer advantages when compared to more common object-oriented languages. Efficiency, security and correctness of programs is easier to ensure in the functional setting. Towards this goal, we design and develop implementation techniques to enable dynamic compilation and optimization of functional programming languages: we describe an intermediate representation for functional programs (typed dynamic continuation-passing style), which is well suited for dynamic compilation. Based on this representation, we have developed an extension for incremental and selective code generation. The main contribution of this work shows how dynamic specialization of polymorphic functions and data structures can increase the run-time efficiency of functional programs considerably. We present the results of experimental measurements for a prototypical implementation, which prove that functional programs can efficiently be dynamically compiled

Extempore: The design, implementation and application of a cyber-physical programming language

There is a long history of experimental and exploratory programming supported by systems that expose interaction through a programming language interface. These live programming systems enable software developers to create, extend, and modify the behaviour of executing software by changing source code without perceptual breaks for recompilation. These live programming systems have taken many forms, but have generally been limited in their ability to express low-level programming concepts and the generation of efficient native machine code. These shortcomings have limited the effectiveness of live programming in domains that require highly efficient numerical processing and explicit memory management. The most general questions addressed by this thesis are what a systems language designed for live programming might look like and how such a language might influence the development of live programming in performance sensitive domains requiring real-time support, direct hardware control, or high performance computing. This thesis answers these questions by exploring the design, implementation and application of Extempore, a new systems programming language, designed specifically for live interactive programming

Higher-Order, Data-Parallel Structured Deduction

State-of-the-art Datalog engines include expressive features such as ADTs (structured heap values), stratified aggregation and negation, various primitive operations, and the opportunity for further extension using FFIs. Current parallelization approaches for state-of-art Datalogs target shared-memory locking data-structures using conventional multi-threading, or use the map-reduce model for distributed computing. Furthermore, current state-of-art approaches cannot scale to formal systems which pervasively manipulate structured data due to their lack of indexing for structured data stored in the heap. In this paper, we describe a new approach to data-parallel structured deduction that involves a key semantic extension of Datalog to permit first-class facts and higher-order relations via defunctionalization, an implementation approach that enables parallelism uniformly both across sets of disjoint facts and over individual facts with nested structure. We detail a core language, $DL_s$, whose key invariant (subfact closure) ensures that each subfact is materialized as a top-class fact. We extend $DL_s$ to Slog, a fully-featured language whose forms facilitate leveraging subfact closure to rapidly implement expressive, high-performance formal systems. We demonstrate Slog by building a family of control-flow analyses from abstract machines, systematically, along with several implementations of classical type systems (such as STLC and LF). We performed experiments on EC2, Azure, and ALCF's Theta at up to 1000 threads, showing orders-of-magnitude scalability improvements versus competing state-of-art systems