Graalvm Enterprise Whitepaper
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The LLVM Instruction Set and Compilation Strategy
The LLVM Instruction Set and Compilation Strategy Chris Lattner Vikram Adve University of Illinois at Urbana-Champaign lattner,vadve ¡ @cs.uiuc.edu Abstract This document introduces the LLVM compiler infrastructure and instruction set, a simple approach that enables sophisticated code transformations at link time, runtime, and in the field. It is a pragmatic approach to compilation, interfering with programmers and tools as little as possible, while still retaining extensive high-level information from source-level compilers for later stages of an application’s lifetime. We describe the LLVM instruction set, the design of the LLVM system, and some of its key components. 1 Introduction Modern programming languages and software practices aim to support more reliable, flexible, and powerful software applications, increase programmer productivity, and provide higher level semantic information to the compiler. Un- fortunately, traditional approaches to compilation either fail to extract sufficient performance from the program (by not using interprocedural analysis or profile information) or interfere with the build process substantially (by requiring build scripts to be modified for either profiling or interprocedural optimization). Furthermore, they do not support optimization either at runtime or after an application has been installed at an end-user’s site, when the most relevant information about actual usage patterns would be available. The LLVM Compilation Strategy is designed to enable effective multi-stage optimization (at compile-time, link-time, runtime, and offline) and more effective profile-driven optimization, and to do so without changes to the traditional build process or programmer intervention. LLVM (Low Level Virtual Machine) is a compilation strategy that uses a low-level virtual instruction set with rich type information as a common code representation for all phases of compilation. -
Analysis of Program Optimization Possibilities and Further Development
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Theoretical Computer Science 90 (1991) 17-36 17 Elsevier Analysis of program optimization possibilities and further development I.V. Pottosin Institute of Informatics Systems, Siberian Division of the USSR Acad. Sci., 630090 Novosibirsk, USSR 1. Introduction Program optimization has appeared in the framework of program compilation and includes special techniques and methods used in compiler construction to obtain a rather efficient object code. These techniques and methods constituted in the past and constitute now an essential part of the so called optimizing compilers whose goal is to produce an object code in run time, saving such computer resources as CPU time and memory. For contemporary supercomputers, the requirement of the proper use of hardware peculiarities is added. In our opinion, the existence of a sufficiently large number of optimizing compilers with real possibilities of producing “good” object code has evidently proved to be practically significant for program optimization. The methods and approaches that have accumulated in program optimization research seem to be no lesser valuable, since they may be successfully used in the general techniques of program construc- tion, i.e. in program synthesis, program transformation and at different steps of program development. At the same time, there has been criticism on program optimization and even doubts about its necessity. On the one hand, this viewpoint is based on blind faith in the new possibilities bf computers which will be so powerful that any necessity to worry about program efficiency will disappear. -
Java Version 40 Download Apache Tomcat ® Welcome to the Apache Tomcat ® 9.X Software Download Page
java version 40 download Apache Tomcat ® Welcome to the Apache Tomcat ® 9.x software download page. This page provides download links for obtaining the latest version of Tomcat 9.0.x software, as well as links to the archives of older releases. Unsure which version you need? Specification versions implemented, minimum Java version required and lots more useful information may be found on the 'which version?' page. Quick Navigation. Release Integrity. You must verify the integrity of the downloaded files. We provide OpenPGP signatures for every release file. This signature should be matched against the KEYS file which contains the OpenPGP keys of Tomcat's Release Managers. We also provide SHA-512 checksums for every release file. After you download the file, you should calculate a checksum for your download, and make sure it is the same as ours. Mirrors. You are currently using https://mirror.softaculous.com/apache/ . If you encounter a problem with this mirror, please select another mirror. If all mirrors are failing, there are backup mirrors (at the end of the mirrors list) that should be available. Please see the README file for packaging information. It explains what every distribution contains. Apache Tomcat ® The Apache Tomcat ® software is an open source implementation of the Jakarta Servlet, Jakarta Server Pages, Jakarta Expression Language, Jakarta WebSocket, Jakarta Annotations and Jakarta Authentication specifications. These specifications are part of the Jakarta EE platform. The Jakarta EE platform is the evolution of the Java EE platform. Tomcat 10 and later implement specifications developed as part of Jakarta EE. Tomcat 9 and earlier implement specifications developed as part of Java EE. -
Optimizing Oracle Database on Oracle Linux with Flash
An Oracle White Paper September 2014 Optimizing Oracle Database Performance on Oracle Linux with Flash Optimizing Oracle Database Performance on Oracle Linux with Flash Introduction ....................................................................................... 1 Advantages of Using Flash-based Caching / Storage with an Oracle Database and Oracle Linux .................................................... 2 Overview of Oracle’s Sun Flash Accelerator PCIe Card .................... 2 Configuring Oracle Linux and the Oracle Database for Optimum I/O Performance ................................................................................ 3 Configure Oracle’s Sun Flash Accelerator PCIe Card as a File System ................................................................................. 3 Configure Oracle ASM Using Multiple Oracle’s Sun Flash Accelerator PCIe Cards for Mirroring or for Increased Smart Flash Cache Capacity ............................................................. 5 Configuring the Oracle Database to Use Database Smart Flash Cache .................................................................................. 5 Oracle 11g Release 2 Database Smart Flash Cache ..................... 6 Database Settings ......................................................................... 9 Benchmark Results ........................................................................... 9 Baseline Results .......................................................................... 10 Results with Database Smart Flash Cache Enabled -
Register Allocation and Method Inlining
Combining Offline and Online Optimizations: Register Allocation and Method Inlining Hiroshi Yamauchi and Jan Vitek Department of Computer Sciences, Purdue University, {yamauchi,jv}@cs.purdue.edu Abstract. Fast dynamic compilers trade code quality for short com- pilation time in order to balance application performance and startup time. This paper investigates the interplay of two of the most effective optimizations, register allocation and method inlining for such compil- ers. We present a bytecode representation which supports offline global register allocation, is suitable for fast code generation and verification, and yet is backward compatible with standard Java bytecode. 1 Introduction Programming environments which support dynamic loading of platform-indep- endent code must provide supports for efficient execution and find a good balance between responsiveness (shorter delays due to compilation) and performance (optimized compilation). Thus, most commercial Java virtual machines (JVM) include several execution engines. Typically, there is an interpreter or a fast com- piler for initial executions of all code, and a profile-guided optimizing compiler for performance-critical code. Improving the quality of the code of a fast compiler has the following bene- fits. It raises the performance of short-running and medium length applications which exit before the expensive optimizing compiler fully kicks in. It also ben- efits long-running applications with improved startup performance and respon- siveness (due to less eager optimizing compilation). One way to achieve this is to shift some of the burden to an offline compiler. The main question is what optimizations are profitable when performed offline and are either guaranteed to be safe or can be easily validated by a fast compiler. -
Graalvm Enterprise Entitlement with Java SE Subscription FAQ
Statement of Direction GraalVM Enterprise Entitlement with Java SE Subscription FAQ Customer Frequently Asked Questions January 2021, Version 1.0 Copyright © 2021, Oracle and/or its affiliates Public 1 GraalVM Enterprise Entitlement with Java SE Subscription FAQ / Version 1.0 Copyright © 2021, Oracle and/or its affiliates / Public Introduction Oracle Java SE Subscription now entitles customers to use Oracle GraalVM Enterprise at no additional cost. General • What are we announcing? o GraalVM Enterprise makes Java SE the preferred development platform for performance-demanding and resource constrained applications, microservices development, and cloud-native environments. Java SE Subscription customers are now immediately entitled to use GraalVM Enterprise in production and for development at no additional cost. • Why are we doing this? o We believe that Java SE Subscription users will greatly benefit from the added value that GraalVM Enterprise provides. • What is GraalVM Enterprise? o Oracle GraalVM Enterprise is a high-performance runtime built on Oracle Java SE that includes an advanced optimizing compiler which can accelerate performance while consuming less memory and CPU resources. It also supports the ahead-of-time compilation of applications into native executables that can start substantially faster and consume significantly less memory and CPU resources than other software platforms, making them ideal for microservices and other containerized applications. Go to the end of the FAQ to learn more about the benefits of GraalVM Enterprise. Learn more at https://www.oracle.com/java/graalvm/. • How does the inclusion of GraalVM Enterprise in the Java SE Subscription affect me if I’m a GraalVM Community Edition user? o GraalVM Community Edition continues to be available. -
Generalizing Loop-Invariant Code Motion in a Real-World Compiler
Imperial College London Department of Computing Generalizing loop-invariant code motion in a real-world compiler Author: Supervisor: Paul Colea Fabio Luporini Co-supervisor: Prof. Paul H. J. Kelly MEng Computing Individual Project June 2015 Abstract Motivated by the perpetual goal of automatically generating efficient code from high-level programming abstractions, compiler optimization has developed into an area of intense research. Apart from general-purpose transformations which are applicable to all or most programs, many highly domain-specific optimizations have also been developed. In this project, we extend such a domain-specific compiler optimization, initially described and implemented in the context of finite element analysis, to one that is suitable for arbitrary applications. Our optimization is a generalization of loop-invariant code motion, a technique which moves invariant statements out of program loops. The novelty of the transformation is due to its ability to avoid more redundant recomputation than normal code motion, at the cost of additional storage space. This project provides a theoretical description of the above technique which is fit for general programs, together with an implementation in LLVM, one of the most successful open-source compiler frameworks. We introduce a simple heuristic-driven profitability model which manages to successfully safeguard against potential performance regressions, at the cost of missing some speedup opportunities. We evaluate the functional correctness of our implementation using the comprehensive LLVM test suite, passing all of its 497 whole program tests. The results of our performance evaluation using the same set of tests reveal that generalized code motion is applicable to many programs, but that consistent performance gains depend on an accurate cost model. -
Efficient Symbolic Analysis for Optimizing Compilers*
Efficient Symbolic Analysis for Optimizing Compilers? Robert A. van Engelen Dept. of Computer Science, Florida State University, Tallahassee, FL 32306-4530 [email protected] Abstract. Because most of the execution time of a program is typically spend in loops, loop optimization is the main target of optimizing and re- structuring compilers. An accurate determination of induction variables and dependencies in loops is of paramount importance to many loop opti- mization and parallelization techniques, such as generalized loop strength reduction, loop parallelization by induction variable substitution, and loop-invariant expression elimination. In this paper we present a new method for induction variable recognition. Existing methods are either ad-hoc and not powerful enough to recognize some types of induction variables, or existing methods are powerful but not safe. The most pow- erful method known is the symbolic differencing method as demonstrated by the Parafrase-2 compiler on parallelizing the Perfect Benchmarks(R). However, symbolic differencing is inherently unsafe and a compiler that uses this method may produce incorrectly transformed programs without issuing a warning. In contrast, our method is safe, simpler to implement in a compiler, better adaptable for controlling loop transformations, and recognizes a larger class of induction variables. 1 Introduction It is well known that the optimization and parallelization of scientific applica- tions by restructuring compilers requires extensive analysis of induction vari- ables and dependencies -
The Effect of Code Expanding Optimizations on Instruction Cache Design
May 1991 UILU-EN G-91-2227 CRHC-91-17 Center for Reliable and High-Performance Computing THE EFFECT OF CODE EXPANDING OPTIMIZATIONS ON INSTRUCTION CACHE DESIGN William Y. Chen Pohua P. Chang Thomas M. Conte Wen-mei W. Hwu Coordinated Science Laboratory College of Engineering UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN Approved for Public Release. Distribution Unlimited. UNCLASSIFIED____________ SECURITY ¿LASSIPlOvriON OF t h is PAGE REPORT DOCUMENTATION PAGE 1a. REPORT SECURITY CLASSIFICATION 1b. RESTRICTIVE MARKINGS Unclassified None 2a. SECURITY CLASSIFICATION AUTHORITY 3 DISTRIBUTION/AVAILABILITY OF REPORT 2b. DECLASSIFICATION/DOWNGRADING SCHEDULE Approved for public release; distribution unlimited 4. PERFORMING ORGANIZATION REPORT NUMBER(S) 5. MONITORING ORGANIZATION REPORT NUMBER(S) UILU-ENG-91-2227 CRHC-91-17 6a. NAME OF PERFORMING ORGANIZATION 6b. OFFICE SYMBOL 7a. NAME OF MONITORING ORGANIZATION Coordinated Science Lab (If applicable) NCR, NSF, AMD, NASA University of Illinois N/A 6c ADDRESS (G'ty, Staff, and ZIP Code) 7b. ADDRESS (Oty, Staff, and ZIP Code) 1101 W. Springfield Avenue Dayton, OH 45420 Urbana, IL 61801 Washington DC 20550 Langley VA 20200 8a. NAME OF FUNDING/SPONSORING 8b. OFFICE SYMBOL ORGANIZATION 9. PROCUREMENT INSTRUMENT IDENTIFICATION NUMBER 7a (If applicable) N00014-91-J-1283 NASA NAG 1-613 8c. ADDRESS (City, State, and ZIP Cod*) 10. SOURCE OF FUNDING NUMBERS PROGRAM PROJECT t a sk WORK UNIT 7b ELEMENT NO. NO. NO. ACCESSION NO. The Effect of Code Expanding Optimizations on Instruction Cache Design 12. PERSONAL AUTHOR(S) Chen, William, Pohua Chang, Thomas Conte and Wen-Mei Hwu 13a. TYPE OF REPORT 13b. TIME COVERED 14. OATE OF REPORT (Year, Month, Day) Jl5. -
Hotspot Java Download
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Current State of EA and Its Uses in The
Jfokus 2020 Current state of EA and Charlie Gracie Java Engineering Group at Microsoft its uses in the JVM Overview • Escape Analysis and Consuming Optimizations • Current State of Escape Analysis in JVM JITs • Escape Analysis and Allocation Elimination in Practice • Stack allocation 2 Escape Analysis and Consuming Optimizations 3 What is Escape Analysis? • Escape Analysis is a method for determining the dynamic scope of objects -- where in the program an object can be accessed. • Escape Analysis determines all the places where an object can be stored and whether the lifetime of the object can be proven to be restricted only to the current method and/or thread. 4 https://en.wikipedia.org/wiki/Escape_analysis Partial Escape Analysis • A variant of Escape Analysis which tracks object lifetime along different control flow paths of a method. • An object can be marked as not escaping along one path even though it escapes along a different path. 5 https://en.wikipedia.org/wiki/Escape_analysis EA Consuming Optimizations 1. Monitor elision • If an object does not escape the current method or thread, then operations can be performed on this object without synchronization 2. Stack allocation • If an object does not escape the current method, it may be allocated in stack memory instead of heap memory 3. Scalar replacement • Improvement to (2) by breaking an object up into its scalar parts which are just stored as locals 6 Current State of Escape Analysis in JVM JITs 7 HotSpot C2 EA and optimizations • Flow-insensitive1 implementation based on the -
Nosql + SQL = Mysql Nicolas De Rico – Principal Solutions Architect [email protected]
NoSQL + SQL = MySQL Nicolas De Rico – Principal Solutions Architect [email protected] Copyright © 2018 Oracle and/or its affiliates. All rights reserved. Safe Harbor Statement The following is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, and timing of any features or functionality described for Oracle’s products remains at the sole discretion of Oracle. Copyright © 2018 Oracle and/or its affiliates. All rights reserved. What If I Told You… ? ? NoSQL + SQL ? …is possible? ? Copyright © 2018 Oracle and/or its affiliates. All rights reserved. MySQL 8.0 The MySQL Document Store Copyright © 2018 Oracle and/or its affiliates. All rights reserved. MySQL 8.0 MySQL 5.0 MySQL 5.1 MySQL 5.5 MySQL 5.6 MySQL 5.7 MySQL 8.0 • MySQL AB • Sun • Improved • Robust • Native JSON • Document Microsystems Windows OS replication • Cost-based Store • Performance • Stricter SQL optimizer • Data Schema • Stronger • Group dictionary • Semi-sync repl security Replication • OLAP NDB Cluster 6.2, 6.3, 7.0, 7.1, 7.2, 7.3, 7.4, 7.5, 7.6, 7.6 Copyright © 2018 Oracle and/or its affiliates. All rights reserved. MySQL Open Source (…Because It Makes Sense) • GPLv2 – Slightly modified for FOSS and OpenSSL – No extraneously restrictive licensing • MySQL source code available on Github – MySQL Receives many contributions from community and partners – Development collaboration with some leading MySQL users • Open Core business model – Additional tools and extensions available in Enterprise Edition – Server and client are GPL open source • This also helps to keep the ecosystem open source Copyright © 2018 Oracle and/or its affiliates.