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187
Pin: building customized program analysis tools with dynamic instrumentation
- IN PLDI ’05: PROCEEDINGS OF THE 2005 ACM SIGPLAN CONFERENCE ON PROGRAMMING LANGUAGE DESIGN AND IMPLEMENTATION
, 2005
"... Robust and powerful software instrumentation tools are essential for program analysis tasks such as profiling, performance evaluation, and bug detection. To meet this need, we have developed a new instrumentation system called Pin. Our goals are to provide easy-to-use, portable, transparent, and eff ..."
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Cited by 991 (35 self)
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Robust and powerful software instrumentation tools are essential for program analysis tasks such as profiling, performance evaluation, and bug detection. To meet this need, we have developed a new instrumentation system called Pin. Our goals are to provide easy-to-use, portable, transparent, and efficient instrumentation. Instrumentation tools (called Pintools) are written in C/C++ using Pin’s rich API. Pin follows the model of ATOM, allowing the tool writer to analyze an application at the instruction level without the need for detailed knowledge of the underlying instruction set. The API is designed to be architecture independent whenever possible, making Pintools source compatible across different architectures. However, a Pintool can access architecture-specific details when necessary. Instrumentation with Pin is mostly transparent as the application and Pintool observe the application’s original, uninstrumented behavior. Pin uses dynamic compilation to instrument executables while they are running. For efficiency, Pin uses several techniques, including inlining, register re-allocation, liveness analysis, and instruction scheduling to optimize instrumentation. This fully automated approach delivers significantly better instrumentation performance than similar tools. For example, Pin is 3.3x faster than Valgrind and 2x faster than DynamoRIO for basic-block counting. To illustrate Pin’s versatility, we describe two Pintools in daily use to analyze production software. Pin is publicly available for Linux platforms on four architectures: IA32 (32-bit x86), EM64T (64-bit x86), Itanium R ○ , and ARM. In the ten months since Pin 2 was released in July 2004, there have been over 3000 downloads from its website.
Escape analysis for Java
- OOPSLA
, 1999
"... This paper presents a simple and efficient data flow algorithm for escape analysis of objects in Java programs to determine (i) if an object can be allocated on the stack; (ii) if an object is accessed only by a single thread duriing its lifetime, so that synchronization operations on that object ca ..."
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Cited by 300 (12 self)
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This paper presents a simple and efficient data flow algorithm for escape analysis of objects in Java programs to determine (i) if an object can be allocated on the stack; (ii) if an object is accessed only by a single thread duriing its lifetime, so that synchronization operations on that object can be removed. We introduce a new program abstraction for escape analysis, the connection graph, that is used to establish reachability rela-tionships between objects and object references. We show that the connection graph can be summarized for each method such that the same summary information may be used effectively in different calling contexts. We present an interprocedural al-gorithm that uses the above property to efficiently compute the connection graph and identify the non-escaping objects for methods and threads. The experimental results, from a proto-type implementation of our framework in the IBM High Per-formance Compiler for Java, are very promising. The percent-age of objects that may be allocated on the stack exceeds 70% of all dynamically created objects in three out of the ten bench-marks (with a median of 19%), 11 % to 92 % of all lock oper-ations are eliminated in those ten programs (with a median of 5 l%), and the overall execution time reduction ranges from 2 % to 23 % (with a median of 7%) on a 333 MHz PowerPC workstation with 128 MB memory. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advant-age and that copies bear this notice and the full citation on the first page.
Compositional Pointer and Escape Analysis for Java Programs
- In Proceedings of the 14th Annual Conference on Object-Oriented Programming Systems, Languages and Applications
, 1999
"... algorithm for Java programs. The algorithm is based on the abstraction of points-to escape graphs, which characterize how local variables and elds in objects refer to other objects. Each points-to escape graph also contains escape information, which characterizes how objects allocated in one region ..."
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Cited by 267 (29 self)
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algorithm for Java programs. The algorithm is based on the abstraction of points-to escape graphs, which characterize how local variables and elds in objects refer to other objects. Each points-to escape graph also contains escape information, which characterizes how objects allocated in one region of the program can escape to be accessed by another region. The algorithm is designed to analyze arbitrary regions of complete or incomplete programs, obtaining complete information for objects that do not escape the analyzed regions.
A Framework for Reducing the Cost of Instrumented Code
- In SIGPLAN Conference on Programming Language Design and Implementation
, 2001
"... Instrumenting code to collect profiling information can cause substantial execution overhead. This overhead makes instrumentation difficult to perform at runtime, often preventing many known offline feedback-directed optimizations from being used in online systems. This paper presents a general fram ..."
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Cited by 195 (10 self)
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Instrumenting code to collect profiling information can cause substantial execution overhead. This overhead makes instrumentation difficult to perform at runtime, often preventing many known offline feedback-directed optimizations from being used in online systems. This paper presents a general framework for performing instrumentation sampling to reduce the overhead of previously expensive instrumentation. The framework is simple and effective, using code-duplication and counter-based sampling to allow switching between instrumented and non-instrumented code.
Adaptive Optimization in the Jalapeno JVM
- In ACM SIGPLAN Conference on Object-Oriented Programming Systems, Languages, and Applications (OOPSLA
, 2000
"... (*58()9$"2#$:0/,;58(03<10/2,>=?33@">"29 #A:0*/,B58(*C2"258/052,D3*>#$,,6-*0'/ 58@F,058*,+HG?!"*0"I"252J58K0/ ,6-*0'/ 030"6N*IO40"58DP)"58QF,058SRUT6252,D<0!2T6252,V52!8("9 "W5X3,06*9E,'Y58(*03C:0'/ X3,06 ..."
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Cited by 181 (14 self)
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(*58()9$"2#$:0/,;58(03<10/2,>=?33@">"29 #A:0*/,B58(*C2"258/052,D3*>#$,,6-*0'/ 58@F,058*,+HG?!"*0"I"252J58K0/ ,6-*0'/ 030"6N*IO40"58DP)"58QF,058SRUT6252,D<0!2T6252,V52!8("9 "W5X3,06*9E,'Y58(*03C:0'/ X3,06*9E,'Y58(*03C 1622 *'\,20/2XD3Q#$,U-0/269EU,/52,X"58QF,0'58,+ I,2/2-K58X^528-3L2T6252,_0/252/,58('4-*0'2,Y 0C#$,058Z#>58,0@=`58a02T/2*(*C/,':b(/,058c+ \",25C0d@"3,152058[#;58!*03e0/252,/58( 5805f8(""52<00"58>b(3589$3,3*"*58QF058C-02,;"(3T Y2520'58258/,03@20'Q"3+ ] D,Q"...
Implementing Jalapeno in Java
, 1999
"... Jalape~no is a virtual machine for Java TM servers written in Java. A running Java program involves four layers of functionality: the user code, the virtual-machine, the operating system, and the hardware. By drawing the Java / non-Java boundary below the virtual machine rather than above it, Jal ..."
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Cited by 109 (4 self)
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Jalape~no is a virtual machine for Java TM servers written in Java. A running Java program involves four layers of functionality: the user code, the virtual-machine, the operating system, and the hardware. By drawing the Java / non-Java boundary below the virtual machine rather than above it, Jalape~no reduces the boundary-crossing overhead and opens up more opportunities for optimization. To get Jalape~no started, a boot image of a working Jalape ~no virtual machine is concocted and written to a file. Later, this file can be loaded into memory and executed. Because the boot image consists entirely of Java objects, it can be concocted by a Java program that runs in any JVM. This program uses reflection to convert the boot image into Jalape~no's object format. A special Magic class allows unsafe casts and direct access to the hardware. Methods of this class are recognized by Jalape~no's three compilers, which ignore their bytecodes and emit special-purpose machine code. User code w...
Virtual Machine Support for Dynamic Join Points. In: AOSD’04,
, 2004
"... ABSTRACT A widespread implementation approach for the join point mechanism of aspect-oriented languages is to instrument areas in code that match the static part of pointcut designators, inserting dynamic checks for that part of matching that depends on run-time conditions, if needed. For performan ..."
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Cited by 99 (16 self)
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ABSTRACT A widespread implementation approach for the join point mechanism of aspect-oriented languages is to instrument areas in code that match the static part of pointcut designators, inserting dynamic checks for that part of matching that depends on run-time conditions, if needed. For performance reasons, such dynamic checks should be avoided whenever possible. One way to do so is to postpone weaving of advice calls until run-time, when conditions determining the emergence of join points hold. This calls for fluid code---code that adapts itself to the join point emergence at run-time, and suggests that AOP concepts should be integrated into the execution model underlying a VM. In this paper, we present first steps toward such an integration in Steamloom, an extension of IBM's Jikes Research Virtual Machine. Steamloom is fairly restricted, but our initial experimental results indicate that aspect-aware VMs and fluid code are promising w.r.t performance. While the focus in this paper is on performance, there are other advantages of aspect-aware VMs to be investigated in the future.
Safe futures for Java
- In Proceedings of the 20th Annual ACM SIGPLAN Conference on Object-Oriented Programming, Systems, Languages, and Applications (OOPSLA 2005). ACM
, 2005
"... A future is a simple and elegant abstraction that allows concurrency to be expressed often through a relatively small rewrite of a sequential program. In the absence of side-effects, futures serve as benign annotations that mark potentially concurrent regions of code. Unfortunately, when computation ..."
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Cited by 96 (7 self)
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A future is a simple and elegant abstraction that allows concurrency to be expressed often through a relatively small rewrite of a sequential program. In the absence of side-effects, futures serve as benign annotations that mark potentially concurrent regions of code. Unfortunately, when computation relies heavily on mutation as is the case in Java, its meaning is less clear, and much of its intended simplicity lost. This paper explores the definition and implementation of safe futures for Java. One can think of safe futures as truly transparent annotations on method calls, which designate opportunities for concurrency. Serial programs can be made concurrent simply by replacing standard method calls with future invocations. Most significantly, even though some parts of the program are executed concurrently and may indeed operate on shared data, the semblance of serial execution is nonetheless preserved. Thus, program reasoning is simplified since data dependencies present in a sequential program are not violated in a version augmented with safe futures. Besides presenting a programming model and API for safe futures, we formalize the safety conditions that must be satisfied to ensure equivalence between a sequential Java program and its futureannotated counterpart. A detailed implementation study is also provided. Our implementation exploits techniques such as object versioning and task revocation to guarantee necessary safety conditions. We also present an extensive experimental evaluation of our implementation to quantify overheads and limitations. Our experiments indicate that for programs with modest mutation rates on shared data, applications can use futures to profitably exploit parallelism, without sacrificing safety.
Software profiling for hot path prediction: less is more
- SIGPLAN Not
"... Recently, there has been a growing interest in exploiting profile information in adaptive systems such as just-in-time compilers, dynamic optimizers and, binary translators. In this paper, we show that sophisticated software profiling schemes that provide highly accurate information in an offline se ..."
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Cited by 80 (1 self)
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Recently, there has been a growing interest in exploiting profile information in adaptive systems such as just-in-time compilers, dynamic optimizers and, binary translators. In this paper, we show that sophisticated software profiling schemes that provide highly accurate information in an offline setting are ill-suited for these dynamic code generation systems. We experimentally demonstrate that hot path predictions must be made early in order to control the rising cost of missed opportunity that result from the prediction delay. We also show that existing sophisticated path profiling schemes, if used in an online setting, offer no prediction advantages over simpler schemes that exhibit much lower runtime overheads. Based on these observation we developed a new low-overhead software profiling scheme for hot path prediction. Using an abstract metric we compare our scheme to path profile based prediction and show that our scheme achieves comparable prediction quality. In our second set of experiments we include runtime overhead and evaluate the performance of our scheme in a realistic application: Dynamo, a dynamic optimization system. The results show that our prediction scheme clearly outperforms path profile based prediction and thus confirm that less profiling as exhibited in our scheme will actually lead to more effective hot path prediction. 1.
A brief history of just-in-time
- ACM Computing Surveys
"... Software systems have been using “just-in-time ” compilation (JIT) techniques since the 1960s. Broadly, JIT compilation includes any translation performed dynamically, after a program has started execution. We examine the motivation behind JIT compilation and constraints imposed on JIT compilation s ..."
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Cited by 79 (2 self)
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Software systems have been using “just-in-time ” compilation (JIT) techniques since the 1960s. Broadly, JIT compilation includes any translation performed dynamically, after a program has started execution. We examine the motivation behind JIT compilation and constraints imposed on JIT compilation systems, and present a classification scheme for such systems. This classification emerges as we survey forty years of JIT work, from