点间确定别名及其在Java程序数据依赖分析中的应用

堆内存的大量使用使得Java程序上数据依赖关系的精确提取仍存在许多困难.对于堆空间上的依赖提取,通常的做法是先对堆上空间进行命名,再据此分析依赖关系.然而该方法不能在多个定义间进行强更新,故分析精度不够理想.针对此问题,该文首先提出了一种点间确定别名的概念,然后用它生成强更新和相对更新来精化数据依赖分析.实验表明,与不进行强更新和相对更新的数据依赖分析方法相比,新算法能够在相对较少的额外时间消耗内,有效地提高堆空间上依赖分析的精度.     

Implementing heap‐object behavior prediction efficiently and effectively

Heap‐allocated objects play an important role in many modern programs. Various results have shown the overall performance of these programs can be improved by increasing the reference locality of heap‐allocated objects. In this paper we describe an approach that improves the virtual memory performance of allocation‐intensive C programs by predicting the reference behavior and lifetime of heap objects as they are allocated. We further describe an implementation of our prediction algorithm and evaluate its performance on real programs. As part of our implementation, we present a low‐overhead algorithm to minimize the cost of gathering run‐time stack information. Finally, we show that an implementation of these algorithms has little overhead and can improve the virtual memory and TLB performance of programs substantially. Copyright © 2001 John Wiley & Sons, Ltd.     

A new approach to pointer analysis for assignments

Pointer analysis is a technique to identify at copile-time the potential values of the pointer expressions in a program,which promises significant benefits for optimzing and parallelizing complilers.In this paper,a new approach to pointer analysis for assignments is presented.In this approach,assignments are classified into three categories:pointer assignments,structure(union)assignents and normal assignments which don‘t affect the point-to information.Pointer analyses for these three kinds of assignments respectively make up the integrated algorithm.When analyzing a pointer assigemtn.a new method called expression expansion is used to calculate both the left targets and the right targets.The integration of recursive data structure analysis into pointer analysis is a significant originality of this paper,which uniforms the pointer analysis for heap variables and the pointer analysis for stack variables.This algorithm is implemented in Agassiz,an analyzing tool for C programs developed by Institute of Parallel Processing,Fudan University,Its accuracy and effectiveness are illustrated by experimental data.     

内存泄漏对象检测与度量方法

程序运行过程中一些不再被使用的对象未及时释放会引发内存泄漏问题,泄漏对象经过长期累积会降低系统性能,甚至导致系统崩溃。针对Java程序中的内存泄漏问题,提出了一种内存泄漏对象检测与度量方法。通过动态跟踪源程序的执行过程,周期性记录堆栈信息,并分析堆中可疑的泄漏对象。定义内存泄漏度计算方法,度量不同对象对程序泄漏的影响程度,从而确定产生泄漏的对象。最后选取两个开源程序进行验证,并与两种现有方法进行对比,结果表明该方法的泄漏检测率较高。     

Automatic Extraction of Heap Reference Properties in Object-Oriented Programs

We present a new technique for helping developers understand heap referencing properties of object-oriented programs and how the actions of the program affect these properties. Our dynamic analysis uses the aliasing properties of objects to synthesize a set of roles; each role represents an abstract object state intended to be of interest to the developer. We allow the developer to customize the analysis to explore the object states and behavior of the program at multiple different and potentially complementary levels of abstraction. The analysis uses roles as the basis for three abstractions: role transition diagrams, which present the observed transitions between roles and the methods responsible for the transitions; role relationship diagrams, which present the observed referencing relationships between objects playing different roles; and enhanced method interfaces, which present the observed roles of method parameters. Together, these abstractions provide useful information about important object and data structure properties and how the actions of the program affect these properties. We have implemented the role analysis and have used this implementation to explore the behavior of several Java programs. Our experience indicates that, when combined with a powerful graphical user interface, roles are a useful abstraction for helping developers explore and understand the behavior of object-oriented programs.     

A mostly‐copying collector component for class templates

Class templates represent a difficulty for C++ garbage collectors since relevant information is available only very late, at instantiation time. Current collectors therefore either fail to work with class templates or have to run in a non‐optimized mode. This paper introduces the template garbage collector (TGC), the first mostly‐copying collector that can handle class templates. It discusses the design decisions that are suggested by the specifics of generic template programming and presents performance results and memory measurements of tests with MTL and GTL, two generic C++ libraries based on the Standard Template Library. The tests show that TGC substantially improves the run times of programs with many small objects with short lifetimes or large objects with long lifetimes. The memory usage at the same time is reasonable. Since TGC modifies the mostly‐copying technique, the heap sizes are in many cases considerably smaller than they are for traditional mostly‐copying collectors. The tests also show that TGC is competitive with the Boehm–Demers–Weiser collector, the most widely used collector for C++. Copyright © 2001 John Wiley & Sons, Ltd.     

静态性能分析的训练集自动生成工具

本文详细介绍了训练集自动生成技术并人出了测试结果,该工具已经作为性能预测器的一部分集成在了我们开发的交互式ＦＯＲＴＲＡＮ并行优系统ＴＩＰＳ中。     

Lock Coarsening: Eliminating Lock Overhead in Automatically Parallelized Object-Based Programs

Atomic operations are a key primitive in parallel computing systems. The standard implementation mechanism for atomic operations uses mutual exclusion locks. In an object-based programming system, the natural granularity is to give each object its own lock. Each operation can then make its execution atomic by acquiring and releasing the lock for the object that it accesses. But this fine lock granularity may have high synchronization overhead because it maximizes the number of executed acquire and release constructs. To achieve good performance it may be necessary to reduce the overhead by coarsening the granularity at which the computation locks objects.In this article we describe a static analysis technique—lock coarsening—designed to automatically increase the lock granularity in object-based programs with atomic operations. We have implemented this technique in the context of a parallelizing compiler for irregular, object-based programs and used it to improve the generated parallel code. Experiments with two automatically parallelized applications show these algorithms to be effective in reducing the lock overhead to negligible levels. The results also show, however, that an overly aggressive lock coarsening algorithm may harm the overall parallel performance by serializing sections of the parallel computation. A successful compiler must therefore negotiate a trade-off between reducing lock overhead and increasing the serialization.     

基于方法调用一般化模型的并行性分析

该文给出了一种考虑了面向对象语言的多态和对象引用别名问题的对象方法间并行性的分析方法，这种方法用于面向对象语言并行化中的并行性分析，文中首先给出了一般化的方法调用模型，然后基于该模型给出了表达式化简，过程和过程间分析的算法，该算法可以求出变量的定义和使用集合，由于并行性分析，该文给出的简单例子即可以将该文的和相关的工作加以区别。其技术已经在作者研制的Java并行化编译器JAPS－Ⅱ中实现。     

基于嵌套循环分类的并行识别技术

传统的分布存储并行编译系统大多是在共享存储并行编译系统的基础上开发的.共享存储并行编译系统的并行识别技术适合OpenMP代码生成,实现方式是将所有嵌套循环都按照相同的识别方法进行处理,用于分布存储并行编译系统必然会导致无法高效发掘程序的并行性.分布存储并行编译系统应根据嵌套循环结构的特点进行分类处理,提出适合MPI代码生成的并行识别技术.为解决上述问题,根据嵌套循环的结构和MPI并行程序的特点,提出了一种新的嵌套循环分类方法,并针对不同的嵌套循环分别提出了相应的并行识别技术.实验结果表明,与采用传统并行识别技术的分布存储并行编译系统相比,按照所提方法对嵌套循环进行分类,采用相应并行识别技术的编译系统能够更高效地识别基准程序中的并行循环,自动生成的MPI并行代码其性能加速比提高了20%以上.     

C‐strider: type‐aware heap traversal for C

Researchers have proposed many tools and techniques that work by traversing the heap, including checkpointing systems, heap profilers, heap assertion checkers, and dynamic software updating systems. Yet building a heap traversal for C remains difficult, and to our knowledge, extant services have used their own application‐specific traversals. This paper presents C‐strider, a framework for writing C heap traversals and transformations. Writing a basic C‐strider service requires implementing only four callbacks; C‐strider then generates a program‐specific traversal that invokes the callbacks as each heap location is visited. Critically, C‐strider is type aware – it tracks types as it walks the heap, so every callback is supplied with the exact type of the associated location. We used C‐strider to implement heap serialization, dynamic software updating, heap checking, and profiling, and then applied the resulting traversals to several programs. We found that C‐strider requires little programmer effort, and the resulting services are efficient and effective. Copyright © 2015 John Wiley & Sons, Ltd.     

分布存储系统中优化通信的冗余计算分割

针对并行循环套序列，提出一种冗余计算分割的通信优化方法，根据数据流分析，文中给出用以确定每个循环套的冗余计算量的一般方法，并在此基础上提出冗余计算分割的实现和判定，针对规则依赖的程序，该文还提出了一个高效的冗余计算分割的实现方法，该技术已经在一个并行编译器中实现，试验结果表明，它比传统的通信优化技术有明显的优越性。     

Auto-CFD-NOW: A pre-compiler for effectively parallelizing CFD applications on networks of workstations

Computational Fluid Dynamics (CFD) applications are highly demanding for parallel computing. Many such applications have been shifted from expensive MPP boxes to cost-effective Networks of Workstations (NOW). Auto-CFD-NOW is a pre-compiler that transforms Fortran CFD sequential programs to efficient message-passing parallel programs running on NOW. Our work makes the following three unique contributions. First, this pre-compiler is highly automatic, requiring a minimum number of user directives for parallelization. Second, we have applied a dependency analysis technique for the CFD applications, called analysis after partitioning. We propose a mirror-image decomposition technique to parallelize self-dependent field loops that are hard to parallelize by existing methods. Finally, traditional optimizations of communication focus on eliminating redundant synchronizations. We have developed an optimization scheme which combines all the non-redundant synchronizations in CFD programs to further reduce the communication overhead. The Auto-CFD-NOW has been implemented on networks of workstations and has been successfully used for automatically parallelizing structured CFD application programs. Our experiments show its effectiveness and scalability for parallelizing large CFD applications. This work is supported in part by the China National Aerospace Science Foundation, and by the U.S. National Science Foundation under grants CCR-9812187, CCR-0098055, CCF-0325760, CCF 0514078, and CNS 0549006.     

A customisable memory management framework for C++

Automatic garbage collection relieves programmers from the burden of managing memory themselves and several techniques have been developed that make garbage collection feasible in many situations, including real time applications or within traditional programming languages. However, optimal performance cannot always be achieved by a uniform general purpose solution. Sometimes an algorithm exhibits a predictable pattern of memory usage that could be better handled specifically, delaying as much as possible the intervention of the general purpose collector. This leads to the requirement for algorithm specific customisation of the collector strategies. We present a dynamic memory management framework which can be customised to the needs of an algorithm, while preserving the convenience of automatic collection in the normal case. The Customisable Memory Manager (CMM) organises memory in multiple heaps. Each heap is an instance of C++ class which abstracts and encapsulates a particular storage discipline. The default heap for collectable objects uses the technique of mostly copying garbage collection, providing good performance and memory compaction. Customisation of the collector is achieved exploiting object orientation by defining specialised versions of the collector methods for each heap class. The object-oriented interface to the collector enables coexistence and coordination among the various collectors as well as integration with traditional code unaware of garbage collection. The CMM is implemented in C++ without any special support in the language or the compiler. The techniques used in the CMM are general enough to be applicable also to other languages. The performance of the CMM is analysed and compared to other conservative collectors for C/C++ in various configurations. © 1998 John Wiley & Sons, Ltd.     

基于动态行为分析的网页木马检测方法

网页木马是一种在网页中插入攻击脚本,利用浏览器及其插件中的漏洞,使受害者的系统静默地下载并安装恶意程序的攻击形式.本文结合动态程序分析和机器学习方法,提出了基于动态行为分析的网页木马检测方法.首先,针对网页木马攻击中的着陆页上的攻击脚本获取行为,监控动态执行函数执行,包括动态生成函数执行、脚本插入、页面插入和URL跳转,并根据一套规则提取这些行为,此外提取与其相关的字符串操作记录作为特征.其次,针对利用堆恶意操作注入shellcode的行为,提出堆危险指标作为特征.最后从Alexa和VirusShare收集了500个网页样本作为数据集,用机器学习方法训练分类模型.实验结果表明：与现有方法相比,文中方法具有准确率高（96.94%）、能有效对抗代码混淆的干扰（较低的误报率6.1%和漏报率1.3%）等优点.     

Automatic Parallelization of Recursive Procedures

Parallelizing compilers have traditionally focussed mainly on parallelizing loops. This paper presents a new framework for automatically parallelizing recursive procedures that typically appear in divide-and-conquer algorithms. We present compile-time analysis, using powerful, symbolic array section analysis, to detect the independence of multiple recursive calls in a procedure. This allows exploitation of a scalable form of nested parallelism, where each parallel task can further spawn off parallel work in subsequent recursive calls. We describe a runtime system which efficiently supports this kind of nested parallelism without unnecessarily blocking tasks. We have implemented this framework in a parallelizing compiler, which is able to automatically parallelize programs like quicksort and mergesort, written in C. For cases where even the advanced compile-time analysis we describe is not able to prove the independence of procedure calls, we propose novel techniques for speculative runtime parallelization, which are more efficient and powerful in this context than analogous techniques proposed previously for speculatively parallelizing loops. Our experimental results on an IBM G30 SMP machine show good speedups obtained by following our approach.     

Efficient Symbolic Analysis for Parallelizing Compilers and Performance Estimators

Symbolic analysis is of paramount importance for parallelizing compilers and performance estimators to examine symbolic expressions with program unknowns such as machine and problem sizes and to solve queries based on systems of constraints (equalities and inequalities). This paper describes novel techniques for counting the number of solutions to a system of constraints, simplifying systems of constraints, computing lower and upper bounds of symbolic expressions, and determining the relationship between symbolic expressions. All techniques target wide classes of linear and non-linearsymbolic expressions and systems of constraints. Our techniques have been implemented and are used as part of a parallelizing compiler and a performance estimator to support analysis and optimization of parallel programs. Various examples and experiments demonstrate the effectiveness of our symbolic analysis techniques.