|Publication number||US7360205 B2|
|Application number||US 10/073,628|
|Publication date||Apr 15, 2008|
|Filing date||Feb 11, 2002|
|Priority date||Feb 9, 2001|
|Also published as||US7392515, US7730001, US8108841, US20020111697, US20020154551, US20020165901, US20080163163|
|Publication number||073628, 10073628, US 7360205 B2, US 7360205B2, US-B2-7360205, US7360205 B2, US7360205B2|
|Inventors||Douglas N. Kimelman, Vadakkedathu T. Rajan, Tova Roth, Vugranam C. Sreedhar, Mark N. Wegman|
|Original Assignee||International Business Machines Corporation|
|Export Citation||BiBTeX, EndNote, RefMan|
|Patent Citations (25), Non-Patent Citations (9), Classifications (23), Legal Events (3)|
|External Links: USPTO, USPTO Assignment, Espacenet|
This application claims the benefit of U.S. Provisional Application No. 60/267,573, filed Feb. 9, 2001.
The present application is related to the present inventors' applications entitled “Characterization Of Objects Of A Computer Program While Running Same” Ser. No. 10/073,573, and “Program Components Having Multiple Selectable Implementations” Ser. No. 10/073,630, which were filed on the same day as the present application. These related application are incorporated herein by reference.
1. Field of the Invention
This invention generally relates to the field of optimization of computer programs, and more particularly relates to a computer system that transforms programs so that they run more quickly or otherwise at lower cost, but produce the same results, by minimizing costs of interaction among program components.
2. Description of Related Art
Programmers are increasingly programming by component assembly. This is despite the fact that the use of components tend to decrease the performance of the program. The programers who design the components do not know anything about the environment the components will be used in, and can therefore not tailor the components for each specific use. The efficiency of a program suffers from the use of such generic components, since it fundamentally depends on the interactions between the components. The performance of a component based program is therefore often less than optimal. Optimizing component interaction is a fundamental problem in constructing efficient component-oriented programs.
Many computer programs, which consist of a number of program components, manipulate implementation properties such as string representations and data structure for which any of a number of implementation properties can be used. For example, string representations that can be used include: UNICODE, ASCII, and EBCDIC. As another example, data structures that can be used include: trees, compressed files and hash tables. In fact, in many database and virtual machine benchmarks, substantial amounts of time are lost in converting data representation values back and forth between a number of different representations.
One problem solved by this invention is that of minimizing the number of transformations of implementation property values, such as data structure values, back and forth over the course of a run of a computer program.
For consistency of definition in the context of the present application, it should be understood that the term “property”, with respect to an object or component of a computer program, is broad, and includes narrower terms such as “location”, “parameter”, and “implementation”. In turn, “implementation” includes “data representation” such as “string representation” (e.g. ASCII, EBCDIC, UNICODE) and “data structure” (e.g. hash, tree, compressed). Thus, it will be understood that “implementation” does not encompass “location”, nor“parameter” within its meaning. Moreover, in the context of the present invention, “object”, “entity”, and “component” shall be interpreted as having substantially the same meaning, while “library” shall be understood to mean a group of object definitions or component definitions.
The present invention broadly provides a method for minimizing total cost of interaction among components of a computer program, each of the components being characterized by at least one implementation property. The method comprises the steps of:
According to another preferred embodiment, the aforesaid data representation property comprises a choice of data structure (e.g. hash tree, and compressed data structures) of a component, the aforesaid amount of interaction measured in step (b) comprising a frequency of interaction between each pair of interacting components; the aforesaid cost of interaction comprising a function of the aforesaid frequency and a cost of converting any differing choices of data structures of the pair to a common choice of data structure.
According to another preferred embodiment, the aforesaid implementation property comprises a choice of data structure (e.g. hash tree, and compressed data structures) of a component, the aforesaid amount of interaction measured in step (b) comprising a frequency of interaction between each pair of interacting components; the aforesaid cost of interaction comprising a function of the aforesaid frequency and a cost of converting any differing choices of data structures of the pair to a common choice of data structure.
Preferably, step (d) of determining the choice is carried out by a mathematical solution, as by building a graph with nodes representing program components and edges that join adjacent nodes representing interaction therebetween, each edge being characterized by a cost of each interaction, then using a graph cutting technique to find a minimum cut of the graph. Such graph cutting techniques are described in three U.S. patent application Ser. Nos. 09/676,423 by Rajan et al, 09/676,424 by Wegman et al, and 09/676,425 by Roth et al, all filed on Sep. 29, 2000.
The invention also comprises a computer readable medium including computer instructions for carrying out each method disclosed herein for minimizing total cost of interaction among components of a computer program running on a computer system.
According to a preferred embodiment of the present invention, a computer system and method (e.g. by instrumenting the program itself, or by instrumenting the system on which the program runs), monitors a representative run of a program (i.e. a run which is similar to the kind of run for which the program is to be optimized—both in terms of the way the program is invoked, and in terms of kind of input data it is given). During the monitored run, the system notes the source variable, the destination variable, and the amount of data moved, for each operation in which data flows from one variable into another.
During or after the run, use this information to construct a graph as follows. For each variable seen during the run, create a non-terminal node corresponding to it. For each flow of data between two variables, create an edge between the two non-terminal nodes corresponding to the two variables, if such an edge does not already exist, and add to the weight of that edge an amount proportional to the amount of data that flowed. For all possible representations of data values seen during the run, create a terminal node corresponding to each such representation. For each use of a variable in an interface to an external program that required that variable to have a particular implementation, one may add an edge between the non-terminal node corresponding to that variable and the terminal node corresponding to the representation, with an infinite weight, if such an edge does not already exist.
Having constructed the graph, one may perform a multi-terminal minimum cut of the graph by any practical means. For each resulting partition, one per terminal node, one should transform the program so that in future runs of the program, each variable corresponding to non-terminal node in the partition will use the representation corresponding to the terminal node of the partition.
The following is a specific exemplary embodiment of the present invention Consider the case in which we are trying to minimizing the cost of running a comprising program components a, b, c, d, e, and f, which may be implemented in two implementations, in this case the string representations ASCII and UNICODE, as shown in
In the example of
The cost values shown in
As will be understood, the OAG graph of
The future runs of the same program on this network of computers should be run with this implementation of components e and f to minimize the cost of running the program on the network.
As will now be understood from this example, the methods described in the three above-cited patent applications have the advantage of being able to find a cut quickly. This allows problems of a given size to be solved more quickly, and it allows larger problems to be solved within a given time constraint (problems which might not have been practical to even attempt to solve otherwise). A graph consists of nodes and edges. Each edge connects two nodes. A weight is associated with each edge. Some of the nodes are designated as being “terminal” nodes. The others are designated as being “non-terminal” nodes.
For use in optimizing data structure value representation conversion: each terminal node can represent a possible representation; each non-terminal node can represent a variable (the representation used by a particular variable is fixed over the course of the entire run); and the weight of each edge between two non-terminal nodes can represent the amount of data that was assigned back and forth over the course of a run between the variables corresponding to the two nodes that the edge connects, or the amount of work needed to convert that data. An edge between a non-terminal node and a terminal node can represent the fact that, due to external interface requirements, the variable corresponding to the non-terminal node must use the representation corresponding to the terminal node. In this case, the edge would be given infinite weight.
A multiway cut of a graph is the set of edges which, when removed from the graph, results in there no longer being a path through the graph from any terminal to any other terminal. A multiway minimum cut of a graph is a cut, the sum of the weights of whose edges is less than or equal to that of any other such cut. Such a cut partitions a graph into one partition for each terminal node. The partition for a terminal node consist of all non-terminal nodes connected to it directly, or indirectly via other non-terminal nodes.
In optimizing data structure value representation conversion, the non-terminal nodes in a partition represent variables that should use the representation corresponding to the terminal node of the partition, in order to keep representation conversions to a minimum, and hence to achieve best overall performance of the program.
The preferred embodiments of the present invention can be realized in hardware, software, or a combination of hardware and software. Any kind of computer system—or other apparatus adapted for carrying out the methods described herein—is suited. A typical combination of hardware and software could be a general purpose computer system with a computer program that, when being loaded and executed, controls the computer system such that it carries out the methods described herein.
The present invention can also be embedded in a computer program product, which comprises all the features enabling the implementation of the methods described herein, and which—when loaded in a computer system—is able to carry out these methods. Computer program means or computer program in the present context mean any expression, in any language, code or notation, of a set of instructions intended to cause a system having an information processing capability to perform a particular function either directly or after either or both of the following a) conversion to another language, code or, notation; and b) reproduction in a different material form.
Each computer system may include, inter alia, one or more computers and at least a computer readable medium allowing a computer to read data, instructions, messages or message packets, and other computer readable information from the computer readable medium. The computer readable medium may include nonvolatile memory, such as ROM, Flash memory, Disk drive memory, CD-ROM, and other permanent storage. Additionally, a computer medium may include, for example, volatile storage such as RAM, buffers, cache memory, and network circuits. Furthermore, the computer readable medium may include computer readable information in a transitory state medium such as a network link and/or a network interface, including a wired network or a wireless network, that allow a computer to read such computer readable information.
Although specific embodiments of the invention have been disclosed, those having ordinary skill in the art will understand that changes can be made to the specific embodiments without departing from the spirit and scope of the invention. The scope of the invention is not to be restricted, therefore, to the specific embodiments, and it is intended that the appended claims cover any and all such applications, modifications, and embodiments within the scope of the present invention.
|Cited Patent||Filing date||Publication date||Applicant||Title|
|US5325533 *||Jun 28, 1993||Jun 28, 1994||Taligent, Inc.||Engineering system for modeling computer programs|
|US5555201 *||Feb 10, 1994||Sep 10, 1996||Lsi Logic Corporation||Method and system for creating and validating low level description of electronic design from higher level, behavior-oriented description, including interactive system for hierarchical display of control and dataflow information|
|US5598559 *||May 28, 1996||Jan 28, 1997||Hewlett-Packard Company||Method and apparatus for optimizing queries having group-by operators|
|US5764989 *||Feb 29, 1996||Jun 9, 1998||Supercede, Inc.||Interactive software development system|
|US6092180 *||Nov 26, 1997||Jul 18, 2000||Digital Equipment Corporation||Method for measuring latencies by randomly selected sampling of the instructions while the instruction are executed|
|US6173437 *||Jul 24, 1997||Jan 9, 2001||Intervoice Limited Partnership||Multimedia scripting tool|
|US6269474 *||Sep 30, 1998||Jul 31, 2001||Veronex Technologies, Inc.||Software re-engineering system|
|US6356890 *||Aug 1, 2000||Mar 12, 2002||Microsoft Corporation||Merging materialized view pairs for database workload materialized view selection|
|US6360360 *||Feb 8, 1996||Mar 19, 2002||International Business Machines Corporation||Object-oriented compiler mechanism for automatically selecting among multiple implementations of objects|
|US6405361 *||Aug 19, 1999||Jun 11, 2002||Manfred Broy||Automatically generating a program|
|US6481008 *||Jun 30, 1999||Nov 12, 2002||Microsoft Corporation||Instrumentation and optimization tools for heterogeneous programs|
|US6530075||Dec 3, 1998||Mar 4, 2003||International Business Machines Corporation||JIT/compiler Java language extensions to enable field performance and serviceability|
|US6546553 *||Jul 8, 1999||Apr 8, 2003||Microsoft Corporation||Service installation on a base function and provision of a pass function with a service-free base function semantic|
|US6550053 *||Apr 5, 2000||Apr 15, 2003||International Computers Limited||Time estimator for object oriented software development|
|US6553565 *||Apr 23, 1999||Apr 22, 2003||Sun Microsystems, Inc||Method and apparatus for debugging optimized code|
|US6615166 *||May 27, 1999||Sep 2, 2003||Accenture Llp||Prioritizing components of a network framework required for implementation of technology|
|US6715130 *||Oct 5, 1998||Mar 30, 2004||Lockheed Martin Corporation||Software requirements metrics and evaluation process|
|US6817013 *||Oct 4, 2001||Nov 9, 2004||International Business Machines Corporation||Program optimization method, and compiler using the same|
|US6817014 *||Apr 11, 2001||Nov 9, 2004||Hewlett-Packard Development Company, L.P.||Analysis of executable program code using compiler-generated function entry points and endpoints with other sources of function entry points and endpoints|
|US6981257 *||Jan 18, 2002||Dec 27, 2005||Teubner Russell W||System, method and apparatus to allow communication between CICS and non-CICS software applications|
|US7028293 *||Mar 30, 2001||Apr 11, 2006||Microsoft Corporation||Constant return optimization transforming indirect calls to data fetches|
|US7082599 *||Jan 14, 2000||Jul 25, 2006||Measurement Computing Corporation||Method and apparatus for detecting and resolving circularflow paths in graphical programming systems|
|US20020154551||Feb 11, 2002||Oct 24, 2002||International Business Machines Corporation||Program components having multiple selectable implementations|
|US20030009401 *||Apr 29, 2002||Jan 9, 2003||Enerwise Global Technologies, Inc.||Computerized utility cost estimation method and system|
|US20060206882 *||Jun 8, 2005||Sep 14, 2006||Daniel Illowsky||Method and system for linear tasking among a plurality of processing units|
|1||*||Clark, Cost modeling process maturity-COCOMO 2.0, IEEE ,vol. 3 , Feb. 3-10, 1996, pp. 347-369 vol. 3.|
|2||*||Hogstedt et al., Optimizing Component Interaction, http://www.research.ibm.com/people/w/wegman/ompdf/vision.pdf, 2001, pp. 1-6.|
|3||*||Keahey et al., PAWS: collective interactions and data transfers, IEEE, Aug. 7-9, 2001 pp. 47-54.|
|4||*||Lederer et al., A causal model for software estimating error, IEEE Transactions on ,vol. 24 , Issue: 2 , Feb. 1998 □□pp. 137-148.|
|5||*||Mili et al., Tracking, predicting and assessing software reuse costs: an automated tool, Jun. 4-11, 2000, IEEE, pp. 785.|
|6||*||New directions in compiler technology for embedded systems, Dutt, N.; Nicolau, A., Tomiyama, H.; Halambi, A., Design Automation Conference, 2001. Proceedings of the ASP-DAC 2001. Asia and South Pacific, 2001, IEEE, pp. 409-414.|
|7||*||Pillai et al., A model for software development effort and cost estimation, IEEE Transactions on ,vol. 23, Issue: 8 , Aug. 1997, pp. 485-497.|
|8||*||Retrospective exploration of safety properties in real-time concurrent systems, Prywes, N.; Rehmet, P.; Sokolsky, O.; Lee, I., Digital Avionics Systems Conference, 1997. 16th DASC., AIAA/IEEE, vol. 1 Oct. 26-30, 1997, IEEE, pp. 1.1-43 to 1.1-51 vol. 1.|
|9||*||Software architectural specification for optimal object distribution, Bastarrica, M.C.; Demurjian, S.A.; Shvartsman, A.A., Computer Science, 1998. SCCC '98. XVIII International Conference of the Chilean Society of, Nov. 9-14, 1998, IEEE, pp. 1-7.|
|U.S. Classification||717/130, 717/151, 700/5, 714/E11.2, 702/108, 714/E11.192, 717/141, 717/153|
|International Classification||G06F9/00, G11C29/00, G06F9/46, G06F15/16, G06F9/44, G01D3/00, G06F19/00, G05B19/18, G06F11/34|
|Cooperative Classification||G06F11/3447, G06F11/3466, G06F2201/865, G06F11/3409|
|European Classification||G06F11/34C, G06F11/34T|
|Feb 11, 2002||AS||Assignment|
Owner name: INTERNATIONAL BUSINESS MACHINES CORPORATION, NEW Y
Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:KIMELMAN, DOUGLAS N.;RAJAN, VADAKKEDATHU T.;ROTH, TOVA;AND OTHERS;REEL/FRAME:012596/0312
Effective date: 20020206
|Jul 15, 2011||FPAY||Fee payment|
Year of fee payment: 4
|Nov 27, 2015||REMI||Maintenance fee reminder mailed|