Instruction Fetching: Coping with Code Bloat
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Debloating Modern Java Applications a Thesis Submitted In
UNIVERSITY OF CALIFORNIA Los Angeles JShrink: Debloating Modern Java Applications A thesis submitted in partial satisfaction of the requirements for the degree Master of Science in Computer Science by Jaspreet Singh Arora 2020 c Copyright by Jaspreet Singh Arora 2020 ABSTRACT OF THE THESIS JShrink: Debloating Modern Java Applications by Jaspreet Singh Arora Master of Science in Computer Science University of California, Los Angeles, 2020 Professor Miryung Kim, Chair Modern software is bloated. Demand for new functionality has led developers to include more and more features, many of which become unneeded or unused as software evolves. This phenomenon of software bloat results in software consuming more resources than it otherwise needs to. Automation of effective debloating is a long standing problem in soft- ware engineering. Various software debloating techniques have been proposed since the late 1990s. However, many of these techniques are built upon pure static analysis and have yet to be extended and evaluated in the context of modern Java applications where dynamic language features are prevalent. To this end, we develop an end-to-end bytecode debloating framework called JShrink. JShrink augments traditional static reachability analysis with dynamic profiling and type dependency analysis, and renovates existing byte-code transfor- mations to perform effective debloating. We highlight several nuanced technical challenges that must be handled properly to debloat modern Java applications and further examine behavior preservation of debloated -
Efficient Processing of Deep Neural Networks
Efficient Processing of Deep Neural Networks Vivienne Sze, Yu-Hsin Chen, Tien-Ju Yang, Joel Emer Massachusetts Institute of Technology Reference: V. Sze, Y.-H.Chen, T.-J. Yang, J. S. Emer, ”Efficient Processing of Deep Neural Networks,” Synthesis Lectures on Computer Architecture, Morgan & Claypool Publishers, 2020 For book updates, sign up for mailing list at http://mailman.mit.edu/mailman/listinfo/eems-news June 15, 2020 Abstract This book provides a structured treatment of the key principles and techniques for enabling efficient process- ing of deep neural networks (DNNs). DNNs are currently widely used for many artificial intelligence (AI) applications, including computer vision, speech recognition, and robotics. While DNNs deliver state-of-the- art accuracy on many AI tasks, it comes at the cost of high computational complexity. Therefore, techniques that enable efficient processing of deep neural networks to improve key metrics—such as energy-efficiency, throughput, and latency—without sacrificing accuracy or increasing hardware costs are critical to enabling the wide deployment of DNNs in AI systems. The book includes background on DNN processing; a description and taxonomy of hardware architectural approaches for designing DNN accelerators; key metrics for evaluating and comparing different designs; features of DNN processing that are amenable to hardware/algorithm co-design to improve energy efficiency and throughput; and opportunities for applying new technologies. Readers will find a structured introduction to the field as well as formalization and organization of key concepts from contemporary work that provide insights that may spark new ideas. 1 Contents Preface 9 I Understanding Deep Neural Networks 13 1 Introduction 14 1.1 Background on Deep Neural Networks . -
UNIVERSITY of CALIFORNIA, SAN DIEGO Holistic Design for Multi-Core Architectures a Dissertation Submitted in Partial Satisfactio
UNIVERSITY OF CALIFORNIA, SAN DIEGO Holistic Design for Multi-core Architectures A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Computer Science (Computer Engineering) by Rakesh Kumar Committee in charge: Professor Dean Tullsen, Chair Professor Brad Calder Professor Fred Chong Professor Rajesh Gupta Dr. Norman P. Jouppi Professor Andrew Kahng 2006 Copyright Rakesh Kumar, 2006 All rights reserved. The dissertation of Rakesh Kumar is approved, and it is acceptable in quality and form for publication on micro- film: Chair University of California, San Diego 2006 iii DEDICATIONS This dissertation is dedicated to friends, family, labmates, and mentors { the ones who taught me, indulged me, loved me, challenged me, and laughed with me, while I was also busy working on my thesis. To Professor Dean Tullsen for teaching me the values of humility, kind- ness,and caring while trying to teach me football and computer architecture. For always encouraging me to do the right thing. For always letting me be myself. For always believing in me. For always challenging me to dream big. For all his wisdom. And for being an adviser in the truest sense, and more. To Professor Brad Calder. For always caring about me. For being an inspiration. For his trust. For making me believe in myself. For his lies about me getting better at system administration and foosball even though I never did. To Dr Partha Ranganathan. For always being there for me when I would get down on myself. And that happened often. For the long discussions on life, work, and happiness. -
Subroutines and Control Abstraction8
Subroutines and Control Abstraction8 8.4.4 Generics in C++, Java, and C# Though templates were not officially added to C++ until 1990, when the language was almost ten years old, they were envisioned early in its evolution. C# generics, likewise, were planned from the beginning, though they actually didn’t appear until the 2.0 release in 2004. By contrast, generics were deliberately omitted from the original version of Java. They were added to Java 5 (also in 2004) in response to strong demand from the user community. C++Templates EXAMPLE 8.69 Figure 8.13 defines a simple generic class in C++ that we have named an Generic arbiter class in arbiter. The purpose of an arbiter object is to remember the “best instance” C++ it has seen of some generic parameter class T. We have also defined a generic chooser class that provides an operator() method, allowing it to be called like a function. The intent is that the second generic parameter to arbiter should be a subclass of chooser, though this is not enforced. Given these definitions we might write class case_sensitive : chooser<string> { public: bool operator()(const string& a, const string& b){returna<b;} }; ... arbiter<string, case_sensitive> cs_names; // declare new arbiter cs_names.consider(new string("Apple")); cs_names.consider(new string("aardvark")); cout << *cs_names.best() << "\n"; // prints "Apple" Alternatively, we might define a case_insensitive descendant of chooser, whereupon we could write Copyright c 2009 by Elsevier Inc. All rights reserved. 189 CD_Ch08-P374514 [11:51 2009/2/25] SCOTT: Programming Language Pragmatics Page: 189 379–215 190 Chapter 8 Subroutines and Control Abstraction template<class T> class chooser { public: virtual bool operator()(const T& a, const T& b) = 0; }; template<class T, class C> class arbiter { T* best_so_far; C comp; public: arbiter() { best_so_far = 0; } void consider(T* t) { if (!best_so_far || comp(*t, *best_so_far)) best_so_far = t; } T* best() { return best_so_far; } }; Figure 8.13 Generic arbiter in C++. -
Appendix M Historical Perspectives and References
M.1 Introduction M-2 M.2 The Early Development of Computers (Chapter 1) M-2 M.3 The Development of Memory Hierarchy and Protection (Chapter 2 and Appendix B) M-9 M.4 The Evolution of Instruction Sets (Appendices A, J, and K) M-17 M.5 The Development of Pipelining and Instruction-Level Parallelism (Chapter 3 and Appendices C and H) M-27 M.6 The Development of SIMD Supercomputers, Vector Computers, Multimedia SIMD Instruction Extensions, and Graphical Processor Units (Chapter 4) M-45 M.7 The History of Multiprocessors and Parallel Processing (Chapter 5 and Appendices F, G, and I) M-55 M.8 The Development of Clusters (Chapter 6) M-74 M.9 Historical Perspectives and References M-79 M.10 The History of Magnetic Storage, RAID, and I/O Buses (Appendix D) M-84 M Historical Perspectives and References If … history … teaches us anything, it is that man in his quest for knowledge and progress is determined and cannot be deterred. John F. Kennedy Address at Rice University (1962) Those who cannot remember the past are condemned to repeat it. George Santayana The Life of Reason (1905), Vol. 2, Chapter 3 M-2 ■ Appendix M Historical Perspectives and References M.1 Introduction This appendix provides historical background on some of the key ideas presented in the chapters. We may trace the development of an idea through a series of machines or describe significant projects. If you are interested in examining the initial development of an idea or machine or are interested in further reading, references are provided at the end of each section. -
Inlining in Gforth: Early Experiences
Inlining in Gforth: Early Experiences David Gregg M. Anton Ertl∗ Trinity College Dublin TU Wien Abstract icant time1. Therefore, Forth compilers with their need for Many optimizations are easier or more effective for compilation speed have not embraced optimizations straight-line code (basic blocks). Straight-line code beyond basic blocks. E.g., RAFTS [EP96] and in Forth is limited mainly by calls and returns. In- (to our knowledge) VFX perform their optimiza- lining eliminates calls and returns, which in turn tions (e.g., register allocation) only at the basic makes the basic blocks longer, and increases the ef- block level. Cforth [Alm86] and (to the best of fectiveness of other optimizations. In this paper we our knowledge) iForth perform global register al- present a first prototype implementation of ininlin- location of a kind by continuing the current alloca- ing for Gforth. tion across branches and performing reconciliation at control flow joins (not necessarily in a close-to- optimal way). 1 Introduction Another reason why loop-level and global opti- mizations are not very useful for Forth is that the Many code generation tasks and optimizations are main cause of basic block boundaries in Forth is relatively easy to perform on basic blocks (code sec- calls and exits (see Fig. 1). tions with only one entry point and one exit), of- Therefore, if we want to optimize Forth signifi- ten with optimal results (with respect to some opti- cantly beyond basic blocks, it seems that we have to mality criterion). Examples are register allocation, perform interprocedural optimization, which is even static stack caching [EG04a], and superinstruction harder, more complicated and slower than global selection [EG03]; all of these problems are relevant optimization, and not as well researched. -
Instruction Fetching: Coping with Code Bloat
To be presented at the 22nd International Symposium on Computer Architecture,To appear in the June 22nd 18 International - 24, 1995, Symposium Santa Margherita on Computer Ligure, Architecture, Italy. Santa Magherita Ligure, Italy, June, 1995. Instruction Fetching: Coping with Code Bloat Richard Uhlig David Nagle Gesellshaft für Mathematik und Datenverarbeitung (GMD) Department of ECE, Carnegie Mellon University Schloβ Birlinghoven, 53757 Sankt Augustin, Germany Pittsburgh, PA 15213 [email protected] [email protected] Trevor Mudge and Stuart Sechrest Joel Emer EECS Department, University of Michigan Digital Equipment Corporation 1301 Beal Ave., Ann Arbor, Michigan 48109-2122 77 Reed Road HLO2-3/J3, Hudson, MA 01749 {tnm,sechrest}@eecs.umich.edu [email protected] Abstract grams to grow in size and examines the impact of these trends on one important aspect of memory-system design: the fetching of Previous research has shown that the SPEC benchmarks instructions. achieve low miss ratios in relatively small instruction caches. This As application and operating system software evolves to paper presents evidence that current software-development prac- include more features and to become more portable, maintainable tices produce applications that exhibit substantially higher and reliable, it also tends to consume more memory resources. instruction-cache miss ratios than do the SPEC benchmarks. To The “bloating” of code affects a memory-system hierarchy at all represent these trends, we have assembled a collection of applica- levels and in a variety of ways: the larger static sizes of program tions, called the Instruction Benchmark Suite (IBS), that provides executables occupy more disk space; the larger working sets of a better test of instruction-cache performance. -
The C++ Programming Language in Cheminformatics And
Rassokhin J Cheminform (2020) 12:10 https://doi.org/10.1186/s13321-020-0415-y Journal of Cheminformatics REVIEW Open Access The C programming language in cheminformatics++ and computational chemistry Dmitrii Rassokhin* Abstract This paper describes salient features of the C programming language and its programming ecosystem, with emphasis on how the language afects scientifc++ software development. Brief history of C and its predecessor the C language is provided. Most important aspects of the language that defne models of programming++ are described in greater detail and illustrated with code examples. Special attention is paid to the interoperability between C and other high-level languages commonly used in cheminformatics, machine learning, data processing and statistical++ computing. Keywords: Programming languages, C, C , Scientifc computing, Computational chemistry, Cheminformatics ++ Introduction role of being the language that de-facto dominates mod- In recent years, a plethora of high-level domain-specifc ern scientifc software development, even though, at frst and general-purpose programming languages have been glance, this may not be so obvious. In this paper, we will developed to greatly increase the productivity of pro- briefy describe the history of C++ and focus on its main grammers working on various types of software projects. characteristics that make it so special. Scientifc programming, which used to be dominated by Brief history of C and C Fortran up until about mid-1980s, now enjoys a healthy ++ choice of tools, languages and libraries that excel in help- Te predecessor of C++, C was developed in the early ing solve all types of problems computational scientists 1970s by Dennis M. -
Reflecting on Generics for Fortran
Reflecting on Generics for Fortran Magne Haveraaen∗∗ Jaakko Järvi∗ Damian Rousonyy July 23, 2019 Abstract This paper focuses on the benefits of a well-designed generics feature, and points out important design decisions for achieving those benefits. 1. A generics facility needs to be type safe, both for the developer and the user of generic code. 2. Built in (intrinsics) and user defined (derived) types and operations (functions/subrou- tines) need to be treated in the same way as generic arguments. 3. A generics facility needs to allow generic parameter lists to be extended/nested. The note does not discuss technicalities of a specific generics design. It is motivated by the upcoming Fortran discussion in Tokyo (JP) in August 2019. 1 Introduction For the upcoming IEC/ISO WG5 & ANSII J3 Fortran committee meeting in Tokyo August 5- 9 there are several proposals for adding a generics feature. Fortran currently lacks a generic mechanism to allow type and operation parameters to modules, classes and operations (functions and subroutines). This prevents Fortran from providing, e.g., reusable collection classes which are now a standard feature of most other mainstream programming languages. The design space of generics is large, evidenced by how different the generics features of different languages are (see some examples in Appendix A). This paper emphasises a few key demands for such a feature, based on observations of problems and successes of generics in various languages. These demands are crucial if one wishes to unleash the full potential of generic code reuse, going beyond the standard examples of generics (collection classes, etc.). -
The Velocity Compiler: Extracting
THE VELOCITY COMPILER: EXTRACTING EFFICIENT MULTICORE EXECUTION FROM LEGACY SEQUENTIAL CODES MATTHEW JOHN BRIDGES ADISSERTATION PRESENTED TO THE FACULTY OF PRINCETON UNIVERSITY IN CANDIDACY FOR THE DEGREE OF DOCTOR OF PHILOSOPHY RECOMMENDED FOR ACCEPTANCE BY THE DEPARTMENT OF COMPUTER SCIENCE ADVISOR: PROF. DAVID I. AUGUST NOVEMBER 2008 c Copyright by Matthew John Bridges, 2008. All Rights Reserved Abstract Multiprocessor systems, particularly chip multiprocessors, have emerged as the predomi- nant organization for future microprocessors. Systems with 4, 8, and 16 cores are already shipping and a future with 32 or more cores is easily conceivable. Unfortunately, multi- ple cores do not always directly improve application performance, particularly for a single legacy application. Consequently, parallelizing applications to execute on multiple cores is essential. Parallel programming models and languages could be used to create multi-threaded applications. However, moving to a parallel programming model only increases the com- plexity and cost involved in software development. Many automatic thread extraction tech- niques have been explored to address these costs. Unfortunately, the amount of parallelism that has been automatically extracted using these techniques is generally insufficient to keep many cores busy. Though there are many reasons for this, the main problem is that extensions are needed to take full advantage of these techniques. For example, many important loops are not parallelized because the compiler lacks the necessary scope to apply the optimization. Additionally, the sequen- tial programming model forces programmers to define a single legal application outcome, rather than allowing for a range of legal outcomes, leading to conservative dependences that prevent parallelization. This dissertation integrates the necessary parallelization techniques, extending them where necessary, to enable automatic thread extraction. -
Loose Loops Sink Chips
Loose Loops Sink Chips Eric Borch Eric Tune Intel Corporation, VSSAD University of California, San Diego [email protected] Department of Computer Science [email protected] Srilatha Manne Joel Emer Intel Corporation, VSSAD ] [srilatha.manne, joel.emer @intel.com Abstract Stage 11 Stage 21 Stage N Loose Loop This paper explores the concept of micro-architectural Tight Loop loops and discusses their impact on processor pipelines. In particular, we establish the relationship between loose loops and pipeline length and configuration, and show their 2 impact on performance. We then evaluate the load reso- Clock lution loop in detail and propose the distributed register Initiation Resolution algorithm (DRA) as a way of reducing this loop. It de- Stage Stage creases the performance loss due to load mis-speculations Loop Length by reducing the issue-to-execute latency in the pipeline. A new loose loop is introduced into the pipeline by the DRA, Figure 1. Micro-architectural loops but the frequency of mis-speculations is very low. The re- duction in latency from issue to execute, along with a low mis-speculation rate in the DRAresult in up to a 4% to 15% loop resolution stage is the execute stage. Loop length is de- improvement in performance using a detailed architectural fined to be the number of stages traversed by a loop, and the simulator. feedback delay is the time required to communicate from the resolution stage to the initiation stage. Loop delay is the sum of the loop length and feedback delay. Loops with 1 Introduction a loop delay of one are referred to as tight loops; all other loops are referred to as loose loops. -
Jshrink: In-Depth Investigation Into Debloating Modern Java Applications
JShrink: In-Depth Investigation into Debloating Modern Java Applications Bobby R. Bruce∗ Tianyi Zhang∗ Jaspreet Arora University of California, Davis Harvard University University of California, Los Angeles U.S.A U.S.A U.S.A [email protected] [email protected] [email protected] Guoqing Harry Xu Miryung Kim University of California, Los Angeles University of California, Los Angeles U.S.A U.S.A [email protected] [email protected] ABSTRACT KEYWORDS Modern software is bloated. Demand for new functionality has Java bytecode, size reduction, reachability analysis, debloating led developers to include more and more features, many of which ACM Reference Format: become unneeded or unused as software evolves. This phenome- Bobby R. Bruce, Tianyi Zhang, Jaspreet Arora, Guoqing Harry Xu, and Miryung non, known as software bloat, results in software consuming more Kim. 2020. JShrink: In-Depth Investigation into Debloating Modern Java resources than it otherwise needs to. How to effectively and auto- Applications. In Proceedings of the 28th ACM Joint European Software En- matically debloat software is a long-standing problem in software gineering Conference and Symposium on the Foundations of Software Engi- engineering. Various debloating techniques have been proposed neering (ESEC/FSE ’20), November 8–13, 2020, Virtual Event, USA. ACM, New since the late 1990s. However, many of these techniques are built York, NY, USA, 12 pages. https://doi.org/10.1145/3368089.3409738 upon pure static analysis and have yet to be extended and evaluated in the context of modern Java applications where dynamic language 1 INTRODUCTION features are prevalent.