Data centric highly parallel debugging

Abramson, David; Dinh, Minh Ngoc; Kurniawan, Donny; Moench, Bob; DeRose, Luiz

doi:10.1145/1851476.1851491

Cited by 12 publications

(11 citation statements)

References 19 publications

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“…We have devised a solution for this challenge by prerounding floating-point values prior to comparison. This is discussed in more detail elsewhere [4]. Second, all hash functions have the potential to generate false results (i.e., hash signature collisions) because multiple values are mapped onto a single signature.…”

Section: Hash-based Comparison Schemementioning

confidence: 99%

“…These illustrate how decomposed data structures can be compared using the hash-based and P2P schemes. We implement the ideas in a parallel relative debugger called Guard [4], and illustrate the debugging technique with a case study in Section 4. The performance of the system is evaluated on a 20,000 core Cray XE6 machine in Section 5.…”

Section: Introductionmentioning

confidence: 99%

“…Note that the hash-based comparison solution has been described in [4], and its performance was assessed using a simulation (instead of the debugger itself).…”

Section: Introductionmentioning

confidence: 99%

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Scalable Relative Debugging

Dinh

Abramson

Jin

2014

IEEE Trans. Parallel Distrib. Syst.

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Detecting and isolating bugs that arise only at high processor counts is a challenging task. Over a number of years, we have implemented a special debugging method, called "relative debugging," that supports debugging applications as they evolve or are ported to larger machines. It allows a user to compare the state of a suspect program against another reference version even as the number of processors is increased. The innovative idea is the comparison of runtime data to reason about the state of the suspect program. While powerful, a naïve implementation of the comparison phase does not scale to large problems running on large machines. In this paper, we propose two different solutions including a hash-based scheme and a direct point-to-point scheme. We demonstrate the implementation, a case study, as well as the performance, of our techniques on 20K cores of a Cray XE6 system.Index Terms-Parallellism and concurrency, distributed debugging, assertion checkers Ç . M.N. Dinh is with the Faculty

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Section: Hash-based Comparison Schemementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Scalable Relative Debugging

Dinh

Abramson

Jin

2014

IEEE Trans. Parallel Distrib. Syst.

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“…Numerous articles discuss the use of relative debugging, which is not the focus of this paper [7,15]. However, we have leveraged the infrastructure to build a proof of concept assertion debugger, and thus we describe Guard in sufficient detail to illustrate the implementation.…”

Section: Implementation In Guardmentioning

confidence: 99%

“…The following sections discuss the implementation of the dataflow compiler and dataflow engine that support the evaluation of multiple ad-hoc debug-time assertions. There are other important architectural aspects of Guard which interested readers can find full description in other literature [7,15] [16].…”

Section: A Guard Architecturementioning

confidence: 99%

Assertion Based Parallel Debugging

Dinh

Abramson

Kurniawan

et al. 2011

2011 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing

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Abstract-Programminglanguages have advanced tremendously over the years, but program debuggers have hardly changed. Sequential debuggers do little more than allow a user to control the flow of a program and examine its state. Parallel ones support the same operations on multiple processes, which are adequate with a small number of processors, but become unwieldy and ineffective on very large machines. Typical scientific codes have enormous multidimensional data structures and it is impractical to expect a user to view the data using traditional display techniques. In this paper we discuss the use of debug-time assertions, and show that these can be used to debug parallel programs. The techniques reduce the debugging complexity because they reason about the state of large arrays without requiring the user to know the expected value of every element. Assertions can be expensive to evaluate, but their performance can be improved by running them in parallel. We demonstrate the system with a case study finding errors in a parallel version of the Shallow Water Equations, and evaluate the performance of the tool on a 4,096 cores Cray XE6.

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A data‐centric framework for debugging highly parallel applications

et al. 2013

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Contemporary parallel debuggers allow users to control more than one processing thread while supporting the same examination and visualisation operations of that of sequential debuggers. This approach restricts the use of parallel debuggers when it comes to large scale scientific applications run across hundreds of thousands compute cores. First, manually observing the runtime data to detect error becomes impractical because the data is too big. Second, performing expensive but useful debugging operations becomes infeasible as the computational codes become more complex, involving larger data structures, and as the machines become larger. This study explores the idea of a data-centric debugging approach, which could be used to make parallel debuggers more powerful. It discusses the use of ad hoc debug-time assertions that allow a user to reason about the state of a parallel computation. These assertions support the verification and validation of program state at runtime as a whole rather than focusing on that of only a single process state. Furthermore, the debugger's performance can be improved by exploiting the underlying parallel platform because the available compute cores can execute parallel debugging functions, while a program is idling at a breakpoint. We demonstrate the system with several case studies and evaluate the performance of the tool on a 20 000 cores Cray XE6.We review assertion usage under the traditional programming model, thus revealing the potential of using assertions for data-centric debugging in a parallel context. We then introduce and describe three distinctive debug-time assertion templates including general ad hoc assertions, comparative assertions and statistical assertions. Assertions under the traditional programming modelAn assertion is a statement about an intended behaviour of a system's component that must be verified during execution. In computer programming, a programmer defines an assertion to ensure a specific state of the program at runtime. Further, using assertions, programmers can inject their design intentions such as constraints or contracts into the executable code. As a result, assertions are used extensively for evaluating invariants, checking input parameters and for enhancing program correctness and quality (8). Assertion is an effective tool, not only for design and verification but also for debugging throughout the software-development cycle. The advantages in using assertions for 502 M. N. DINH ET AL.debugging software come from three important attributes: their ability to perform error detection, error isolation and error notification. In addition, assertions support a more data-centric view of debugging because a user does not focus on the control path, but can assert that various data structures should be in particular states at various stages in the program execution. A generic assertion-based parallel debuggerAssertions can also be used as a powerful tool for the debugging purpose. In particular, a programmer writes ad hoc assertions at debug time to tes...

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Data centric highly parallel debugging

Abstract: Abstract

Cited by 12 publications

References 19 publications

Scalable Relative Debugging

Scalable Relative Debugging

Assertion Based Parallel Debugging

A data‐centric framework for debugging highly parallel applications

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