549 research outputs found
A General Framework for Static Profiling of Parametric Resource Usage
Traditional static resource analyses estimate the total resource usage of a
program, without executing it. In this paper we present a novel resource
analysis whose aim is instead the static profiling of accumulated cost, i.e.,
to discover, for selected parts of the program, an estimate or bound of the
resource usage accumulated in each of those parts. Traditional resource
analyses are parametric in the sense that the results can be functions on input
data sizes. Our static profiling is also parametric, i.e., our accumulated cost
estimates are also parameterized by input data sizes. Our proposal is based on
the concept of cost centers and a program transformation that allows the static
inference of functions that return bounds on these accumulated costs depending
on input data sizes, for each cost center of interest. Such information is much
more useful to the software developer than the traditional resource usage
functions, as it allows identifying the parts of a program that should be
optimized, because of their greater impact on the total cost of program
executions. We also report on our implementation of the proposed technique
using the CiaoPP program analysis framework, and provide some experimental
results. This paper is under consideration for acceptance in TPLP.Comment: Paper presented at the 32nd International Conference on Logic
Programming (ICLP 2016), New York City, USA, 16-21 October 2016, 22 pages,
LaTe
12th International Workshop on Termination (WST 2012) : WST 2012, February 19â23, 2012, Obergurgl, Austria / ed. by Georg Moser
This volume contains the proceedings of the 12th International Workshop on Termination (WST 2012), to be held February 19â23, 2012 in Obergurgl, Austria. The goal of the Workshop on Termination is to be a venue for presentation and discussion of all topics in and around termination. In this way, the workshop tries to bridge the gaps between different communities interested and active in research in and around termination. The 12th International Workshop on Termination in Obergurgl continues the successful workshops held in St. Andrews (1993), La Bresse (1995), Ede (1997), Dagstuhl (1999), Utrecht (2001), Valencia (2003), Aachen (2004), Seattle (2006), Paris (2007), Leipzig (2009), and Edinburgh (2010). The 12th International Workshop on Termination did welcome contributions on all aspects of termination and complexity analysis. Contributions from the imperative, constraint, functional, and logic programming communities, and papers investigating applications of complexity or termination (for example in program transformation or theorem proving) were particularly welcome. We did receive 18 submissions which all were accepted. Each paper was assigned two reviewers. In addition to these 18 contributed talks, WST 2012, hosts three invited talks by Alexander Krauss, Martin Hofmann, and Fausto Spoto
Systolic Array Implementations With Reduced Compute Time.
The goal of the research is the establishment of a formal methodology to develop computational structures more suitable for the changing nature of real-time signal processing and control applications. A major effort is devoted to the following question: Given a systolic array designed to execute a particular algorithm, what other algorithms can be executed on the same array? One approach for answering this question is based on a general model of array operations using graph-theoretic techniques. As a result, a systematic procedure is introduced that models array operations as a function of the compute cycle. As a consequence of the analysis, the dissertation develops the concept of fast algorithm realizations. This concept characterizes specific realizations that can be evaluated in a reduced number of cycles. It restricts the operations to remain in the same class but with reduced execution time. The concept takes advantage of the data dependencies of the algorithm at hand. This feature allows the modification of existing structures by reordering the input data. Applications of the principle allows optimum time band and triangular matrix product on arrays designed for dense matrices. A second approach for analyzing the families of algorithms implementable in an array, is based on the concept of array time constrained operation. The principle uses the number of compute cycle as an additional degree of freedom to expand the class of transformations generated by a single array. A mathematical approach, based on concepts from multilinear algebra, is introduced to model the recursive transformations implemented in linear arrays at each compute cycle. The proposed representation is general enough to encompass a large class of signal processing and control applications. A complete analytical model of the linear maps implementable by the array at each compute cycle is developed. The proposed methodology results in arrays that are more adaptable to the changing nature of operations. Lessons learned from analyzing existing arrays are used to design smart arrays for special algorithm realizations. Applications of the methodology include the design of flexible time structures and the ability to decompose a full size array into subarrays implementing smaller size problems
On the synthesis of integral and dynamic recurrences
PhD ThesisSynthesis techniques for regular arrays provide a disciplined and well-founded approach to
the design of classes of parallel algorithms. The design process is guided by a methodology
which is based upon a formal notation and transformations.
The mathematical model underlying synthesis techniques is that of affine Euclidean geometry
with embedded lattice spaces. Because of this model, computationally powerful methods
are provided as an effective way of engineering regular arrays. However, at present the
applicability of such methods is limited to so-called affine problems.
The work presented in this thesis aims at widening the applicability of standard synthesis
methods to more general classes of problems. The major contributions of this thesis are the
characterisation of classes of integral and dynamic problems, and the provision of techniques
for their systematic treatment within the framework of established synthesis methods. The
basic idea is the transformation of the initial algorithm specification into a specification
with data dependencies of increased regularity, so that corresponding regular arrays can be
obtained by a direct application of the standard mapping techniques.
We will complement the formal development of the techniques with the illustration of a
number of case studies from the literature.EPSR
Shape-based cost analysis of skeletal parallel programs
Institute for Computing Systems ArchitectureThis work presents an automatic cost-analysis system for an implicitly parallel skeletal
programming language.
Although deducing interesting dynamic characteristics of parallel programs (and in
particular, run time) is well known to be an intractable problem in the general case, it
can be alleviated by placing restrictions upon the programs which can be expressed.
By combining two research threads, the âskeletalâ and âshapelyâ paradigms which
take this route, we produce a completely automated, computation and communication
sensitive cost analysis system. This builds on earlier work in the area by quantifying
communication as well as computation costs, with the former being derived for the
Bulk Synchronous Parallel (BSP) model.
We present details of our shapely skeletal language and its BSP implementation strategy
together with an account of the analysis mechanism by which program behaviour
information (such as shape and cost) is statically deduced. This information can be
used at compile-time to optimise a BSP implementation and to analyse computation
and communication costs. The analysis has been implemented in Haskell. We consider
different algorithms expressed in our language for some example problems and
illustrate each BSP implementation, contrasting the analysis of their efficiency by traditional,
intuitive methods with that achieved by our cost calculator. The accuracy of
cost predictions by our cost calculator against the run time of real parallel programs is
tested experimentally.
Previous shape-based cost analysis required all elements of a vector (our nestable bulk
data structure) to have the same shape. We partially relax this strict requirement on data
structure regularity by introducing new shape expressions in our analysis framework.
We demonstrate that this allows us to achieve the first automated analysis of a complete
derivation, the well known maximum segment sum algorithm of Skillicorn and Cai
Some advances in the polyhedral model
Department Head: L. Darrell Whitley.2010 Summer.Includes bibliographical references.The polyhedral model is a mathematical formalism and a framework for the analysis and transformation of regular computations. It provides a unified approach to the optimization of computations from different application domains. It is now gaining wide use in optimizing compilers and automatic parallelization. In its purest form, it is based on a declarative model where computations are specified as equations over domains defined by "polyhedral sets". This dissertation presents two results. First is an analysis and optimization technique that enables us to simplify---reduce the asymptotic complexity---of such equations. The second is an extension of the model to richer domains called Æ”-Polyhedra. Many equational specifications in the polyhedral model have reductions---application of an associative and commutative operator to collections of values to produce a collection of answers. Moreover, expressions in such equations may also exhibit reuse where intermediate values that are computed or used at different index points are identical. We develop various compiler transformations to automatically exploit this reuse and simplify the computational complexity of the specification. In general, there is an infinite set of applicable simplification transformations. Unfortunately, different choices may result in equivalent specifications with different asymptotic complexity. We present an algorithm for the optimal application of simplification transformations resulting in a final specification with minimum complexity. This dissertation also presents the Æ”-Polyhedral model, an extension to the polyhedral model to more general sets, thereby providing a transformation framework for a larger set of regular computations. For this, we present a novel representation and interpretation of Æ”-Polyhedra and prove a number of properties of the family of unions of Æ”-Polyhedra that are required to extend the polyhedral model. Finally, we present value based dependence analysis and scheduling analysis for specifications in the Æ”-Polyhedral model. These are direct extensions of the corresponding analyses of specifications in the polyhedral model. One of the benefits of our results in the Æ”-Polyhedral model is that our abstraction allows the reuse of previously developed tools in the polyhedral model with straightforward pre- and post-processing
- âŠ