Applying an abstract data structure description approach to parallelizing scientific pointer programs

Even though impressive progress has been made in the area of parallelizing scientific programs with arrays, the application of similar techniques to programs with pointer data structures has remained difficult. Unlike arrays which have a small number of well-defined properties that can be utilized by a parallelizing compiler, pointer data structures are used to implement a wide variety of structures that exhibit a much more diverse set of properties. The complexity and diversity of such properties means that, in general, scientific programs with pointer data structures cannot be effectively analyzed by an optimizing and parallelizing compiler.In order to provide a system in which the compiler can fully utilize the properties of different types of pointer data structures, we have developed a mechanism for the Abstract Description of Data Structures (ADDS). With our approach, the programmer can explicitly describe important properties such as dimensionality of the pointer data structure, independence of dimensions, and direction of traversal. These abstract descriptions of pointer data structures are then used by the compiler to guide analysis, optimization, and parallelization.In this paper we summarize the ADDS approach through the use of numerous examples of data structures used in scientific computations, we illustrate how such declarations are natural and non-tedious to specify, and we show how the ADDS declarations can be used to improve compile-time analysis. In order to demonstrate the viability of our approach, we show how such techniques can be used to parallelize an important class of scientific codes which naturally use recursive pointer data structures. In particular, we use our approach to develop the parallelization of an N-body simulation that is based on a relatively complicated pointer data structure, and we report the speedup results for a Sequent multiprocessor

Genet: A Quickly Scalable Fat-Tree Overlay for Personal Volunteer Computing using WebRTC

WebRTC enables browsers to exchange data directly but the number of possible concurrent connections to a single source is limited. We overcome the limitation by organizing participants in a fat-tree overlay: when the maximum number of connections of a tree node is reached, the new participants connect to the node's children. Our design quickly scales when a large number of participants join in a short amount of time, by relying on a novel scheme that only requires local information to route connection messages: the destination is derived from the hash value of the combined identifiers of the message's source and of the node that is holding the message. The scheme provides deterministic routing of a sequence of connection messages from a single source and probabilistic balancing of newer connections among the leaves. We show that this design puts at least 83% of nodes at the same depth as a deterministic algorithm, can connect a thousand browser windows in 21-55 seconds in a local network, and can be deployed for volunteer computing to tap into 320 cores in less than 30 seconds on a local network to increase the total throughput on the Collatz application by two orders of magnitude compared to a single core

AspectMatlab++: Annotations, Types, and Aspects for Scientists

Abstract In this paper we present extensions to an aspect oriented compiler developed for MATLAB. These extensions are intended to support important functionality for scientists, and include pattern matching on annotations, and types of variables, as well as new manners of exposing context. We provide use-cases of these features in the form of several general-use aspects which focus on solving issues that arise from use of dynamically-typed languages. We also detail performance enhancements to the ASPECTMATLAB compiler which result in an order of magnitude in performance gains

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A trace monitor observes the sequence of actions in a software system, and when it detects that this sequence matches a given pattern, it executes some extra code of its own. Trace monitors are often specified declaratively using patterns based on regular expressions, context free grammars or logical formulae, and then the trace monitor implementation is generated from the specification. Trace monitors are particularly useful for runtime verification, and many variations have been proposed. Despite this intense interest, there have been hardly any systems that implement the idea in its full generality, because it is hard to generate e#cient code from a purely declarative statement of the pattern. This paper identifies and addresses the challenges faced in generating e#cient trace monitors from declarative pattern-based specifications

Building, scaling, and sustaining a learning health system for surgical quality improvement: A toolkit

This article describes how to start, replicate, scale, and sustain a learning health system for quality improvement, based on the experience of the Michigan Surgical Quality Collaborative (MSQC). The key components to operationalize a successful collaborative improvement infrastructure and the features of a learning health system are explained. This information is designed to guide others who desire to implement quality improvement interventions across a regional network of hospitals using a collaborative approach. A toolkit is provided (under Supporting Information) with practical information for implementation.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/156156/3/lrh210215.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156156/2/lrh210215-sup-0001-supinfo.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156156/1/lrh210215_am.pd

The Truth, the Whole Truth, and Nothing but the Truth: A Pragmatic Guide to Assessing Empirical Evaluations

An unsound claim can misdirect a field, encouraging the pursuit of unworthy ideas and the abandonment of promising ideas. An inadequate description of a claim can make it difficult to reason about the claim, for example to determine whether the claim is sound. Many practitioners will acknowledge the threat of un- sound claims or inadequate descriptions of claims to their field. We believe that this situation is exacerbated and even encouraged by the lack of a systematic approach to exploring, exposing, and addressing the source of unsound claims and poor exposition. This paper proposes a framework that identifies three sins of reasoning that lead to unsound claims and two sins of exposition that lead to poorly described claims. Sins of exposition obfuscate the objective of determining whether or not a claim is sound, while sins of reasoning lead directly to unsound claims. Our framework provides practitioners with a principled way of critiquing the integrity of their own work and the work of others. We hope that this will help individuals conduct better science and encourage a cultural shift in our research community to identify and promulgate sound claims

Context-sensitive points-to analysis: is it worth it

Abstract. We present the results of an empirical study evaluating the precision of subset-based points-to analysis with several variations of context sensitivity on Java benchmarks of significant size. We compare the use of call site strings as the context abstraction, object sensitivity, and the BDD-based context-sensitive algorithm proposed by Zhu and Calman, and by Whaley and Lam. Our study includes analyses that context-sensitively specialize only pointer variables, as well as ones that also specialize the heap abstraction. We measure both characteristics of the points-to sets themselves, as well as effects on the precision of client analyses. To guide development of efficient analysis implementations, we measure the number of contexts, the number of distinct contexts, and the number of distinct points-to sets that arise with each context sensitivity variation. To evaluate precision, we measure the size of the call graph in terms of methods and edges, the number of devirtualizable call sites, and the number of casts statically provable to be safe. The results of our study indicate that object-sensitive analysis implementations are likely to scale better and more predictably than the other approaches; that objectsensitive analyses are more precise than comparable variations of the other approaches; that specializing the heap abstraction improves precision more than extending the length of context strings; and that the profusion of cycles in Java call graphs severely reduces precision of analyses that forsake context sensitivity in cyclic regions.