Exploitation of parallelism to nested loops with dependence cycles

In this paper, we analyze the recurrences from the breakability of the dependence links formed in general multi-statements in a nested loop. The major findings include: (1) A sin k variable renaming technique, which can reposition an undesired anti-dependence and/or output-dependence link, is capable of breaking an anti-dependence and/or output-dependence link. (2) For recurrences connected by only true dependences, a dynamic dependence concept and the derived technique are powerful in terms of parallelism exploitation. (3) By the employment of global dependence testing, link-breaking strategy, Tarjan’s depth-first search algorithm, and a topological sorting, an algorithm for resolving a general multi-statement recurrence in a nested loop is proposed. Experiments with benchmark cited from Vector loops showed that among 134 subroutines tested, 3 had their parallelism exploitation amended by our proposed method. That is, our offered algorithm increased the rate of parallelism exploitation of Vector loops by approximately 2.24%.     

A data dependence test based on the projection of paths over shape graphs

We propose a data dependence detection test based on a new conflict analysis algorithm for C codes which make intensive use of recursive data structures dynamically allocated in the heap. This algorithm requires two pieces of information from the code section under analysis (a loop or a recursive function): (i) abstract shape graphs that represent the state of the heap at the code section; and (ii) path expressions that collect the traversing information for each statement. Our algorithm projects the path expressions on the shape graphs and checks over the graphs to ascertain whether one of the sites reached by a write statement matches one of the sites reached by another statement on a different loop iteration (or on a different call instance in a recursive function), in which case a conflict between the two statements is reported. Although our algorithm presents exponential complexity, we have found that in practice the parameters that dominate the computational cost have very low values, and to the best of our knowledge, all the other related studies involve higher costs. In fact, our experimental results show reductions in the data dependence analysis times of one or two orders of magnitude in some of the studied benchmarks when compared to a previous data dependence algorithm. Thanks to the information on uncovered data dependences, we have manually parallelized these codes, achieving speedups of 2.19 to 3.99 in four cores.     

一种基于特征的程序可并行点发现方法

并行编译技术的首要问题就是程序中可并行点的发现。以程序执行时间、程序中的循环部分、数据依赖性分析以及程序执行时间与循环次数比等特征来表征程序的可并行性,并采用SVM根据以上特征进行程序中的可并行点的挖掘。实验证明,该方法更能符合实际应用的需要,发现的可并行点做并行化后有可观的性能加速比。     

Goal-oriented dynamic test generation

ContextMemory safety errors such as buffer overflow vulnerabilities are one of the most serious classes of security threats. Detecting and removing such security errors are important tasks of software testing for improving the quality and reliability of software in practice.ObjectiveThis paper presents a goal-oriented testing approach for effectively and efficiently exploring security vulnerability errors. A goal is a potential safety violation and the testing approach is to automatically generate test inputs to uncover the violation.MethodWe use type inference analysis to diagnose potential safety violations and dynamic symbolic execution to perform test input generation. A major challenge facing dynamic symbolic execution in such application is the combinatorial explosion of the path space. To address this fundamental scalability issue, we employ data dependence analysis to identify a root cause leading to the execution of the goal and propose a path exploration algorithm to guide dynamic symbolic execution for effectively discovering the goal.ResultsTo evaluate the effectiveness of our proposed approach, we conducted experiments against 23 buffer overflow vulnerabilities. We observed a significant improvement of our proposed algorithm over two widely adopted search algorithms. Specifically, our algorithm discovered security vulnerability errors within a matter of a few seconds, whereas the two baseline algorithms failed even after 30 min of testing on a number of test subjects.ConclusionThe experimental results highlight the potential of utilizing data dependence analysis to address the combinatorial path space explosion issue faced by dynamic symbolic execution for effective security testing.     

Partitioning and mapping of nested loops for linear array multicomputers

In distributed-memory multicomputers, minimizing interprocessor communication is the key to the efficient execution of parallel programs. In order to reduce the amount of communication overhead, parallel programs on multicomputers must be carefully scheduled by parallelizing compilers. This paper proposes some compilation techniques for partitioning and mapping nested loops with constant data dependences onto linear array multicomputers. First, a systematic partition strategy is proposed to project ann-dimensional computational structure, representing ann-nested loop, onto a line to form a one-dimensional projected structure with low communication overhead. Then, a mapping algorithm is proposed for mapping the partitioned loops onto linear arrays in a way that balances the workload and minimizes the communication cost among processors. Finally, parallel execution codes can be automatically generated for such linear array multicomputers.     

OpenMP并行程序的编译器优化

OpemMP标准以其良好的可移植性和易用性被广泛应用于并行程序设计。该文讨论了OpenMP并行程序的编译器优化算法,在编译过程中通过并行区合并和扩展,实现并行区重构,并在并行区中实现了基于跨处理器相关图的barrier同步优化。分析验证表明,这些优化策略减少了并行区和barrier同步的数目,有效地提高了OpenMP程序的并行性能。     

A Compile/Run-time Environment for the Automatic Transformation of Linked List Data Structures

Irregular access patterns are a major problem for today’s optimizing compilers. In this paper, a novel approach will be presented that enables transformations that were designed for regular loop structures to be applied to linked list data structures. This is achieved by linearizing access to a linked list, after which further data restructuring can be performed. Two subsequent optimization paths will be considered: annihilation and sublimation, which are driven by the occurring regular and irregular access patterns in the applications. These intermediate codes are amenable to traditional compiler optimizations targeting regular loops. In the case of sublimation, a run-time step is involved which takes the access pattern into account and thus generates a data instance specific optimized code. Both approaches are applied to a sparse matrix multiplication algorithm and an iterative solver: preconditioned conjugate gradient. The resulting transformed code is evaluated using the major compilers for the x86 platform, GCC and the Intel C compiler.     

基于规范划分集的并行循环编译框架

1 引言并行循环描述大多数先进科学应用的核心部分,是颇有价值的并行性来源。高级并行语言往往提供专门指导语句表达并行循环,以便并行编译器利用并行循环的非数据相关特性。在数据并行程序设计语言HPF中规定,可以将关键词INDEPENDENT加在Do循环前面,指出其后的Do循环是一个并行循环。与之相关的编译实现也成为HPF编译器的一个重点。并行循环L可以严格定义如下:假设R(i)表示迭代i所