Automatic SIMD vectorization for Haskell

The Glasgow Haskell Compiler (GHC) is a well supported optimizing compiler for the Haskell programming language, along with its own extensions to the language and libraries. Haskell's lazy semantics imposes a runtime model which is in general difficult to implement efficiently. GHC achieves good performance across a wide variety of programs via aggressive optimization taking advantage of the lack of side effects, and by targeting a carefully tuned virtual machine. The Intel Labs Haskell Research Compiler uses GHC as a frontend, but provides a new whole-program optimizing backend by compiling the GHC intermediate representation to a relatively generic functional language compilation platform. We found that GHC's external Core language was relatively easy to use, but reusing GHC's libraries and achieving full compatibility were harder. For certain classes of programs, our platform provides substantial performance benefits over GHC alone, performing 2x faster than GHC with the LLVM backend on selected modern performance-oriented benchmarks; for other classes of programs, the benefits of GHC's tuned virtual machine continue to outweigh the benefits of more aggressive whole program optimization. Overall we achieve parity with GHC with the LLVM backend. In this paper, we describe our Haskell compiler stack, its implementation and optimization approach, and present benchmark results comparing it to GHC.

The Glasgow Haskell Compiler (GHC) has quite sophisticated support for concurrency in its runtime system, which is written in low-level C code. As GHC evolves, the runtime system becomes increasingly complex, error-prone, difficult to maintain and difficult to add new concurrency features.This paper presents an alternative approach to implement concurrency in GHC. Rather than hard-wiring all kinds of concurrency features, the runtime system is a thin substrate providing only a small set of concurrency primitives, and the remaining concurrency features are implemented in software libraries written in Haskell. This design improves the safety of concurrency support; it also provides more customizability of concurrency features, which can be developed as Haskell library packages and deployed modularly.

A limited form of dependent types, called Generalized Algebraic Data Types (GADTs), has recently been added to the list of Haskell extensions supported by the Glasgow Haskell Compiler. Despite not being full-fledged dependent types, GADTs still offer considerably enlarged scope for enforcing important code and data invariants statically. Moreover, GADTs offer the tantalizing possibility of writing more efficient programs since capturing invariants statically through the type system sometimes obviates entire layers of dynamic tests and associated data markup. This paper is a case study on the applications of GADTs in the context of Yampa, a domain-specific language for Functional Reactive Programming in the form of a self-optimizing, arrow-based Haskell combinator library. The paper has two aims. Firstly, to explore what kind of optimizations GADTs make possible in this context. Much of that should also be relevant for other domain-specific embedded language implementations, in particular arrow-based ones. Secondly, as the actual performance impact of the GADT-based optimizations is not obvious, to quantify this impact, both on tailored micro benchmarks, to establish the effectiveness of individual optimizations, and on two fairly large, realistic applications, to gauge the overall impact. The performance gains for the micro benchmarks are substantial. This implies that the Yampa API could be simplified as a number of "pre-composed" primitives that were there mainly for performance reasons are no longer needed. As to the applications, a worthwhile performance gain was obtained in one case whereas the performance was more or less unchanged in the other.

We describe a monadic interface to low-level hardware features that is a suitable basis for building operating systems in Haskell. The interface includes primitives for controlling memory management hardware, user-mode process execution, and low-level device I/O. The interface enforces memory safety in nearly all circumstances. Its behavior is specified in part by formal assertions written in a programming logic called P-Logic. The interface has been implemented on bare IA32 hardware using the Glasgow Haskell Compiler (GHC) runtime system. We show how a variety of simple O/S kernels can be constructed on top of the interface, including a simple separation kernel and a demonstration system in which the kernel, window system, and all device drivers are written in Haskell.

Arrows are a popular form of abstract computation. Being more general than monads, they are more broadly applicable, and, in particular, are a good abstraction for signal processing and dataflow computations. Most notably, arrows form the basis for a domain-specific language called Yampa , which has been used in a variety of concrete applications, including animation, robotics, sound synthesis, control systems, and graphical user interfaces. Our primary interest is in better understanding the class of abstract computations captured by Yampa. Unfortunately, arrows are not concrete enough to do this with precision. To remedy this situation, we introduce the concept of commutative arrows that capture a noninterference property of concurrent computations. We also add an init operator that captures the causal nature of arrow effects, and identify its associated law. To study this class of computations in more detail, we define an extension to arrows called causal commutative arrows (CCA), and study its properties. Our key contribution is the identification of a normal form for CCA called causal commutative normal form (CCNF). By defining a normalization procedure, we have developed an optimization strategy that yields dramatic improvements in performance over conventional implementations of arrows. We have implemented this technique in Haskell, and conducted benchmarks that validate the effectiveness of our approach. When compiled with the Glasgow Haskell Compiler (GHC), the overall methodology can result in significant speedups.

The most widely available high performance platforms today are multilevel clusters of multicores. The Glasgow Haskell Compiler (GHC) provides a number of parallel Haskell implementations targeting different parallel architectures. In particular, GHC-SMP supports shared memory, and GHC-GUM supports distributed memory machines. Both implementations use different, but related, runtime environment (RTE) mechanisms. Good performance results can be achieved on shared memory architectures and on networks individually. However, a combination of both, for networks of multicores, is lacking.We present the design and implementation of a new parallel Haskell RTE implementation, GUMSMP, which exploits hierarchical platforms more effectively. It is designed to efficiently combine distributed memory parallelism, using a virtual shared heap over a cluster, with low-overhead shared memory parallelism on the multicores. Key design objectives for realising this system are: asymmetric load balance, effective latency hiding, and mostly passive load distribution.We show that the automatic hierarchical load distribution policies must be carefully tuned to obtain good performance, showing the impact of several policies, including work pre-fetching and favouring inter-node work distribution. We present the initial performance results for this implementation, demonstrating the good scalability of a set of 8 benchmarks on up to 100 cores, and show performance gains of up to 20% compared to GHC-GUM.

We have developed a new, portable I/O event manager for the Glasgow Haskell Compiler (GHC) that scales to the needs of modern server applications. Our new code is transparently available to existing Haskell applications. Performance at lower concurrency levels is comparable with the existing implementation. We support millions of concurrent network connections, with millions of active timeouts, from a single multithreaded program, levels far beyond those achievable with the current I/O manager. In addition, we provide a public API to developers who need to create event-driven network applications.

Programmers need convenient syntax to write elegant and concise programs. Consequently, the Haskell standard provides syntactic sugar for some scenarios (e.g., do notation for monadic code), authors of Haskell compilers provide syntactic sugar for more scenarios (e.g., arrow notation in GHC), and some Haskell programmers implement preprocessors for their individual needs (e.g., idiom brackets in SHE). But manually written preprocessors cannot scale: They are expensive, error-prone, and not composable. Most researchers and programmers therefore refrain from using the syntactic notations they need in actual Haskell programs, but only use them in documentation or papers. We present a syntactically extensible version of Haskell, SugarHaskell, that empowers ordinary programmers to implement and use custom syntactic sugar.Building on our previous work on syntactic extensibility for Java, SugarHaskell integrates syntactic extensions as sugar libraries into Haskell's module system. Syntax extensions in SugarHaskell can declare arbitrary context-free and layout-sensitive syntax. SugarHaskell modules are compiled into Haskell modules and further processed by a Haskell compiler. We provide an Eclipse-based IDE for SugarHaskell that is extensible, too, and automatically provides syntax coloring for all syntax extensions imported into a module.We have validated SugarHaskell with several case studies, including arrow notation (as implemented in GHC) and EBNF as a concise syntax for the declaration of algebraic data types with associated concrete syntax. EBNF declarations also show how to extend the extension mechanism itself: They introduce syntactic sugar for using the declared concrete syntax in other SugarHaskell modules.

CλaSH is a functional hardware description language that borrows both its syntax and semantics from the functional programming language Haskell. Polymorphism and higher-order functions provide a level of abstraction and generality that allow a circuit designer to describe circuits in a more natural way than possible with the language elements found in the traditional hardware description languages. Circuit descriptions can be translated to synthesizable VHDL using the prototype CλaSH compiler. As the circuit descriptions, simulation code, and test input are also valid Haskell, complete simulations can be done by a Haskell compiler or interpreter, allowing high-speed simulation and analysis.

The paper deals with the possibilities of using specialized (virtual labs and simulators, software for natural process simulation) and general (programming languages and libraries, spreadsheets, CAS) software in school researches.Such software as virtual labs, software for natural process simulation, programming languages and libraries in school researches can be used to simulate phenomena that cannot be learned in a school lab (for example, for modeling a radioactive decay or for demonstrating the states of relativistic mechanics). Also, virtual labs in school practice are usually used in those cases where students cannot perform an experiment in real labs. For example, it is convenient for distance learning.The using of programming languages and libraries in physics learning research requires both students’ physics research competencies and programming competencies. That is why using this software in physics classes can hardly be recommended. However, programming languages and libraries can become a powerful tool for the formation and development of research competencies of physics students in extracurricular learning activities.The implementation of the spreadheets and the CAS in school physics researches is the easiest and has its benefits.

PLNoise: a package for exact numerical simulation of power-law noises

By providing increased robustness to failure and reproducibility of results, workflows are an established workhorse of computer-aided science as well as an increasingly important part also in data pipelines in industry. For such complex and dynamic needs, we argue for the benefits of workflows implemented as computer programs, using workflow tools implemented as programming libraries. Furthermore, by using flow-based programming principles, a declarative while programmatic API can be presented, while still hiding a lot of low-level details under the hood. Being able to provide workflows in the form of compiled executable files has benefits both for the ease of deployment and future reproducibility. Workflow tool implementations are at risk for bit rot or incompatible changes well before the mainstream programming languages -or processor architectures -are.

PsN-Toolkit—A collection of computer intensive statistical methods for non-linear mixed effect modeling using NONMEM

The Bulk Synchronous Parallel ML (BSML) is a functional language for BSP programming, a model of computing which allows parallel programs to be ported to a wide range of architectures. It is based on an extension of the ML language by parallel operations on a parallel data structure called parallel vector, which is given by intention. We present a new approach to certifying BSML programs in the context of type theory. Given a specification and a program, an incomplete proof of the specification (of which algorithmic contents corresponds to the given program) is built in the type theory, in which gaps would correspond to the proof obligation. This development demonstrates the usefulness of higher-order logic in the process of software certification of parallel applications. It also shows that the proof of rather complex parallel algorithms may be done with inductive types without great difficulty by using existing certified programs. This work has been implemented in the Coq Proof Assistant, applied on non-trivial examples and is the basis of a certified library of BSML programs.

An Analysis of the Performance of Websockets in Various Programming Languages and Libraries