Actors that Unify Threads and Events

There is an impedance mismatch between message-passing concurrency and virtual machines, such as the JVM. VMs usually map their threads to heavyweight OS processes. Without a lightweight process abstraction, users are often forced to write parts of concurrent applications in an event-driven style which obscures control flow, and increases the burden on the programmer. In this paper we show how thread-based and event-based programming can be unified under a single actor abstraction. Using advanced abstraction mechanisms of the Scala programming language, we implemented our approach on unmodified JVMs. Our programming model integrates well with the threading model of the underlying VM

Relating goal scheduling, precedence, and memory management in and-parallel execution of logic programs

The interactions among three important issues involved in the implementation of logic programs in parallel (goal scheduling, precedence, and memory management) are discussed. A simplified, parallel memory management model and an efficient, load-balancing goal scheduling strategy are presented. It is shown how, for systems which support "don't know" non-determinism, special care has to be taken during goal scheduling if the space recovery characteristics of sequential systems are to be preserved. A solution based on selecting only "newer" goals for execution is described, and an algorithm is proposed for efficiently maintaining and determining precedence relationships and variable ages across parallel goals. It is argued that the proposed schemes and algorithms make it possible to extend the storage performance of sequential systems to parallel execution without the considerable overhead previously associated with it. The results are applicable to a wide class of parallel and coroutining systems, and they represent an efficient alternative to "all heap" or "spaghetti stack" allocation models

Continuation-Passing C: compiling threads to events through continuations

In this paper, we introduce Continuation Passing C (CPC), a programming language for concurrent systems in which native and cooperative threads are unified and presented to the programmer as a single abstraction. The CPC compiler uses a compilation technique, based on the CPS transform, that yields efficient code and an extremely lightweight representation for contexts. We provide a proof of the correctness of our compilation scheme. We show in particular that lambda-lifting, a common compilation technique for functional languages, is also correct in an imperative language like C, under some conditions enforced by the CPC compiler. The current CPC compiler is mature enough to write substantial programs such as Hekate, a highly concurrent BitTorrent seeder. Our benchmark results show that CPC is as efficient, while using significantly less space, as the most efficient thread libraries available.Comment: Higher-Order and Symbolic Computation (2012). arXiv admin note: substantial text overlap with arXiv:1202.324

An Analytical Approach to Programs as Data Objects

This essay accompanies a selection of 32 articles (referred to in bold face in the text and marginally marked in the bibliographic references) submitted to Aarhus University towards a Doctor Scientiarum degree in Computer Science.The author's previous academic degree, beyond a doctoral degree in June 1986, is an "Habilitation à diriger les recherches" from the Université Pierre et Marie Curie (Paris VI) in France; the corresponding material was submitted in September 1992 and the degree was obtained in January 1993.The present 32 articles have all been written since 1993 and while at DAIMI.Except for one other PhD student, all co-authors are or have been the author's students here in Aarhus

Scheme 2003: proceedings of the fourth workshop on scheme and functional programming

technical reportThis report contains the papers presented at the Fourth Workshop on Scheme and Functional Programming. The purpose of the Scheme Workshop is to discuss experience with and future developments of the Scheme programming language?including the future of Scheme standardization?as well as general aspects of computer science loosely centered on the general theme of Scheme

Description and Optimization of Abstract Machines in a Dialect of Prolog

In order to achieve competitive performance, abstract machines for Prolog and related languages end up being large and intricate, and incorporate sophisticated optimizations, both at the design and at the implementation levels. At the same time, efficiency considerations make it necessary to use low-level languages in their implementation. This makes them laborious to code, optimize, and, especially, maintain and extend. Writing the abstract machine (and ancillary code) in a higher-level language can help tame this inherent complexity. We show how the semantics of most basic components of an efficient virtual machine for Prolog can be described using (a variant of) Prolog. These descriptions are then compiled to C and assembled to build a complete bytecode emulator. Thanks to the high level of the language used and its closeness to Prolog, the abstract machine description can be manipulated using standard Prolog compilation and optimization techniques with relative ease. We also show how, by applying program transformations selectively, we obtain abstract machine implementations whose performance can match and even exceed that of state-of-the-art, highly-tuned, hand-crafted emulators.Comment: 56 pages, 46 figures, 5 tables, To appear in Theory and Practice of Logic Programming (TPLP

Relating goal scheduling, precedence, and memory management in and-parallel execution of logic programs

The interactions among three important issues involved in the implementation of logic programs in parallel (goal scheduling, precedence, and memory management) are discussed. A simplified, parallel memory management model and an efficient, load-balancing goal scheduling strategy are presented. It is shown how, for systems which support "don't know" non-determinism, special care has to be taken during goal scheduling if the space recovery characteristics of sequential systems are to be preserved. A solution based on selecting only "newer" goals for execution is described, and an algorithm is proposed for efficiently maintaining and determining precedence relationships and variable ages across parallel goals. It is argued that the proposed schemes and algorithms make it possible to extend the storage performance of sequential systems to parallel execution without the considerable overhead previously associated with it. The results are applicable to a wide class of parallel and coroutining systems, and they represent an efficient alternative to "all heap" or "spaghetti stack" allocation models

Tensor Based Monitoring of Large-Scale Network Traffic

Network monitoring systems are important for network operators to easily analyze behavioral trends in flow data. As networks become larger and more complex, the data becomes more complex with increased size and more variables. This increase in dimensionality lends itself to tensor-based analysis of network data as tensors are arbitrarily sized multi-dimensional objects. Tensor-based network monitoring methods have been explored in recent years through work at Carnegie Mellon University through their algorithm DenseAlert. DenseAlert identifies events anomalous events in tensors through quick detection of dense sub-tensors in positive-valued tensors. However, from experimentation, DenseAlert fails on larger datasets. Drawing from RED Alert, we developed an algorithm called RED Alert that uses recursive filtering and expansion to handle anomaly detection in large tensors of positive and negative valued data. This is done through the use of network parameters that are structured in a hierarchical fashion. That is, network traffic is first modeled at low granular data (e.g. host country), and events detected as anomalous in lower spaces are tracked down to higher granular data (e.g. host IP). The tensors are built on-the-fly in streaming data, filtering data to only consider the parameters deemed anomalous in previous granularity levels. RED Alert is showcased on two network monitoring examples, packet loss detection and botnet detection, comparing results to DenseAlert. In both cases, RED Alert was able to detect suspicious events and identify the root cause of the behavior from a sole IP. RED Alert was developed as part of a greater project, InSight2, that provides several different network monitoring dashboards to aid network operators. This required additional development of a tensor library that worked in the context of InSight2 as well as the development of a dashboard that could run the algorithm and display the results in meaningful ways