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Popcorn Linux: Enabling Efficient Inter-Core Communication in a Linux-Based Multikernel Operating System
Popcorn Linux: enabling efficient inter-core communication in a Linux-based multikernel operating system Benjamin H. Shelton Thesis submitted to the Faculty of the Virginia Polytechnic Institute and State University in partial fulfillment of the requirements for the degree of Master of Science in Computer Engineering Binoy Ravindran Christopher Jules White Paul E. Plassman May 2, 2013 Blacksburg, Virginia Keywords: Operating systems, multikernel, high-performance computing, heterogeneous computing, multicore, scalability, message passing Copyright 2013, Benjamin H. Shelton Popcorn Linux: enabling efficient inter-core communication in a Linux-based multikernel operating system Benjamin H. Shelton (ABSTRACT) As manufacturers introduce new machines with more cores, more NUMA-like architectures, and more tightly integrated heterogeneous processors, the traditional abstraction of a mono- lithic OS running on a SMP system is encountering new challenges. One proposed path forward is the multikernel operating system. Previous efforts have shown promising results both in scalability and in support for heterogeneity. However, one effort’s source code is not freely available (FOS), and the other effort is not self-hosting and does not support a majority of existing applications (Barrelfish). In this thesis, we present Popcorn, a Linux-based multikernel operating system. While Popcorn was a group effort, the boot layer code and the memory partitioning code are the authors work, and we present them in detail here. To our knowledge, we are the first to support multiple instances of the Linux kernel on a 64-bit x86 machine and to support more than 4 kernels running simultaneously. We demonstrate that existing subsystems within Linux can be leveraged to meet the design goals of a multikernel OS. -
Operating Systems – the Code We Love to Hate
U.S. Department of Energy Office of Science Operating Systems – the Code We Love to Hate (Operating and Runtime Systems: Status, Challenges and Futures) Fred Johnson Senior Technical Manager for Computer Science Office of Advanced Scientific Computing Research DOE Office of Science Salishan – April 2005 1 U.S. Department of Energy The Office of Science Office of Science Supports basic research that underpins DOE missions. Constructs and operates large scientific facilities for the U.S. scientific community. Accelerators, synchrotron light sources, neutron sources, etc. Six Offices Basic Energy Sciences Biological and Environmental Research Fusion Energy Sciences High Energy Nuclear Physics Advanced Scientific Computing Research Salishan – April 2005 2 U.S. Department of Energy Simulation Capability Needs -- FY2005 Timeframe Office of Science Sustained Application Simulation Need Computational Significance Capability Needed (Tflops) Climate Calculate chemical balances Provides U.S. policymakers with Science in atmosphere, including > 50 leadership data to support policy clouds, rivers, and decisions. Properly represent and vegetation. predict extreme weather conditions in changing climate. Magnetic Optimize balance between > 50 Underpins U.S. decisions about future Fusion Energy self-heating of plasma and international fusion collaborations. heat leakage caused by Integrated simulations of burning electromagnetic turbulence. plasma crucial for quantifying prospects for commercial fusion. Combustion Understand interactions > 50 Understand detonation dynamics (e.g. Science between combustion and engine knock) in combustion turbulent fluctuations in systems. Solve the “soot “ problem burning fluid. in diesel engines. Environmental Reliably predict chemical > 100 Develop innovative technologies to Molecular and physical properties of remediate contaminated soils and Science radioactive substances. groundwater. Astrophysics Realistically simulate the >> 100 Measure size and age of Universe and explosion of a supernova for rate of expansion of Universe. -
Operating Systems at the Extreme Scale
OperatING SYSTEMS at THE EXTREME SCALE CRESTA White Paper Authors: Daniel Holmes, EPCC, The University of Edinburgh Editors: Erwin Laure KTH Royal Institute of Technology, Mark Parsons and Lorna Smith, EPCC Collaborative Research Into Exascale Systemware, Tools and Applications (CRESTA) ICT-2011.9.13 Exascale computing, software and simulation FOREWORD ABOUT BY DR DANIEL HOLMES, FROM EPCC at THE UNIVERSITY OF EDINBURGH AND CRESTA BY PROFESSOR MARK PARSONS, COORDINatOR OF THE CRESTA PROJect techNical staFF MEMBER. AND EXecutiVE DirectOR at EPCC, THE UNIVERSITY OF EDINBURGH, UK. As we move ever closer to the first exascale systems, understanding the current status of The Collaborative Research into Exascale, Systemware Tools and Applications (CRESTA) project operating system development becomes increasingly important. In particular, being able to quantify is focused on the software challenges of exascale computing, making it a unique project. While the potential impact of the operating system on applications at scale is key. This white paper does a number of projects worldwide are studying hardware aspects of the race to perform 1018 just this, before evaluating and looking to drive developments in operating systems to address calculations per second, no other project is focusing on the exascale software stack in the way that identified scaling issues. we are. The current trend in operating system research and development of re-implementing existing APIs By limiting our work to a small set of representative applications we hope to develop key insights into is likely to continue. However, this approach is incremental and driven by developments in hardware the necessary changes to applications and system software required to compute at this scale. -
HPC System Call Usage Trends
HPC System Call Usage Trends Terry Jones†, Andrew Tauferner‡, Todd Inglett‡ † Lawrence Livermore National Laboratory ‡ International Business Machines P.O. Box 808, L-561 IBM Systems & Technology Group Livermore, CA 94551 Rochester, MN 55901 [email protected] {ataufer , tinglett} @us.ibm.com Abstract. The changing landscape of high performance computing (HPC) hardware and applications poses a constant challenge to operating system architects. In this paper, we assess operating system evolution on the basis of several key factors related to system call functionality. Results are presented for Linux and Linux-like lightweight kernels. Comparisons are made with several other operating systems employed in high performance computing environments including AIX, HP-UX, OpenSolaris, and FreeBSD. Results are provided in tabular form. To our knowledge, this is the first such compilation of system call trends. 1. Introduction A system call is simply the request of an application program for service from the operating system. It is the mechanism through which applications gain access to the operating system kernel – that portion of system software that is permanently memory-resident and responsible for managing system resources such as process scheduling and I/O control. When an application makes a system call, the calling program is making direct use of the facili- ties provided by the kernel and the major portion of system call code is ac- tually executed as part of the kernel itself and not the calling program. [1] We distinguish system calls from library calls in that library calls may be performed without access to the operating system kernel or its data struc- tures; when a program calls a library call, the code executed is part of the final object program (e.g. -
Fusedos: Fusing LWK Performance with FWK Functionality in a Heterogeneous Environment
2012 IEEE 24th International Symposium on Computer Architecture and High Performance Computing FusedOS: Fusing LWK Performance with FWK Functionality in a Heterogeneous Environment Yoonho Park@ Eric Van Hensbergen% Marius Hillenbrand# Todd Inglett∗ Bryan Rosenburg@ Kyung Dong Ryu@ Robert W. Wisniewski+ Abstract environment Linux provides, not the Linux kernel itself. We Traditionally, there have been two approaches to providing an refer to a collection of Linux APIs, personality, etc., as a Linux operating environment for high performance computing (HPC). environment. A Full-Weight Kernel (FWK) approach starts with a general- purpose operating system and strips it down to better scale FusedOS’s design objectives are to address both core het- up across more cores and out across larger clusters. A Light- erogeneity and the need for a rich and familiar operating Weight Kernel (LWK) approach starts with a new thin kernel environment for more applications. We generalize the types code base and extends its functionality by adding more system of compute elements to cores optimized for power efficiency services needed by applications. In both cases, the goal is to (Power-Efficient Cores or PECs), and cores optimized for provide end-users with a scalable HPC operating environment with the functionality and services needed to reliably run their single-thread performance (Single-Thread-Optimized Cores or applications. STOCs). We envision that PECs may have limited capability To achieve this goal, we propose a new approach, called to run traditional kernels (such as GPUs do today), and that FusedOS, that combines the FWK and LWK approaches. applications running on a chip with PECs and STOCs will FusedOS provides an infrastructure capable of partitioning the desire to fully utilize the capability of the chip in a Linux resources of a multicore heterogeneous system and collaboratively environment. -
-- ::E~§: Isg Field Developed Programs
Do not reproduce without written permission FOP 5785-AAA.1 --------- --_ ....- Feb 83 :: -- ::E~§: ISG FIELD DEVELOPED PROGRAMS 3800 PLOTTING FACILITY HOST DEVELOPMENT AND TEST SYSTEM FOR 5785-AAA 8100 COBOL USING TIME SHARING OPTION This FDP, written in FORTRAN, allows the creation of precise drawings 5785-DCF and graphs on the 3800 Plotting Subsystem. It uses simple commands, HOST DEVELOPMENT AND TEST SYSTEM FOR similar to those used for drawings on plotting devices. 8100 COBOL USING CONVERSATIONAL MONITOR SYSTEM The objective of the FDP is to produce on an 3800 Printing Subsystem 5785-DCG more precise drawings and graphs than have been possible using These FOPs are designed for interactive Distributed Processing periods or asterisks on conventional printers. Programming Executive (DPPX)/COBOL program development and Highlights: testing on a host 5/370, 303X or 4300 Processor using a simulated test • Ease of use - the common interfaces to the plotting subroutines are environment. identical, from a parameter standpoint, to those of available plotter Host Development and Test/COBOL processes all DPPX/COBOL packages. source codes including COBOL Structured Programming statements. • Higher quality graphs - the graphics output are of a quality acceptable for final copy in graphs not requiring a high degree of Host Development and Test/COBOL simulates the COBOL-DPS resolution, such as business trend analysis. In addition, it can be Function Management interface as it would appear on an 8100/DPPX used to test programs which produce graphs requiring a high degree System. of resolution, such as engineering drawings. Notices GB21-2570 (DCF) and GB21-2572 (DCG), PDOMs SB21-2571 Notice G821-2154, PDOM S821-2155. -
Mos: an Architecture for Extreme-Scale Operating Systems
mOS: An Architecture for Extreme-Scale Operating Systems Robert W. Wisniewskiy Todd Ingletty Pardo Keppely Ravi Murtyy Rolf Rieseny Linux R , or more specifically, the Linux API, plays a key 1. INTRODUCTION role in HPC computing. Even for extreme-scale computing, As the system software community moves forward to ex- a known and familiar API is required for production ma- ascale computing and beyond, there is the oft debated ques- chines. However, an off-the-shelf Linux distribution faces tion of how revolutionary versus how evolutionary the soft- challenges at extreme scale. To date, two approaches have ware needs to be. Over the last half decade, researchers been used to address the challenges of providing an operat- have pushed in one direction or the other. We contend that ing system (OS) at extreme scale. In the Full-Weight Kernel both directions are valid and needed simultaneously. Throw- (FWK) approach, an OS, typically Linux, forms the starting ing out all current software environments and starting over point, and work is undertaken to remove features from the would be untenable from an application perspective. Yet, environment so that it will scale up across more cores and there are significant challenges getting to exascale and be- out across a large cluster. A Light-Weight Kernel (LWK) yond, so revolutionary approaches are needed. Thus, we approach often starts with a new kernel and work is under- need to simultaneously allow the evolutionary path, i.e., in taken to add functionality to provide a familiar API, typi- the OS context, a Linux API, to coexist with revolutionary cally Linux. -
Early Experiences with KTAU on the IBM BG/L
Early Experiences with KTAU on the IBM BG/L Aroon Nataraj, Allen D. Malony, Alan Morris, and Sameer Shende Performance Research Laboratory, Department of Computer and Information Science University of Oregon, Eugene, OR, USA, {anataraj,malony,amorris,sameer}@cs.uoregon.edu Abstract. The influences of OS and system-specific effects on applica- tion performance are increasingly important in high performance com- puting. In this regard, OS kernel measurement is necessary to under- stand the interrelationship of system and application behavior. This can be viewed from two perspectives: kernel-wide and process-centric. An integrated methodology and framework to observe both views in HPC systems using OS kernel measurement has remained elusive. We demon- strate a new tool called KTAU (Kernel TAU) that aims to provide paral- lel kernel performance measurement from both perspectives. KTAU ex- tends the TAU performance system with kernel-level monitoring, while leveraging TAU’s measurement and analysis capabilities. As part of the ZeptoOS scalable operating systems project, we report early experiences using KTAU in ZeptoOS on the IBM BG/L system. Keywords: Kernel, performance, measurement, analysis. 1 Introduction As High Performance Computing (HPC) moves towards ever larger parallel en- vironments, the influence of OS and system-specific effects on application per- formance are increasingly important to include in a comprehensive performance view. These effects have already been demonstrated ([10], [16]) to be poten- tial bottlenecks, but an integrated methodology and framework to observe their influence relative to application activities and performance has yet to be fully developed. Such an approach will require OS performance monitoring. OS per- formance can be observed from two different perspectives. -
NESL, NDPC (A Home- Grown Language), and Racket
Electrical Engineering and Computer Science Department Technical Report NU-EECS-16-12 September 8, 2016 Hybrid Runtime Systems Kyle C. Hale Abstract As parallelism continues to increase in ubiquity—from mobile devices and GPUs to datacenters and supercomputers—parallel runtime systems occupy an increasingly impor- tant role in the system software stack. The needs of parallel runtimes and the increasingly sophisticated languages and compilers they support do not line up with the services pro- vided by general-purpose OSes. Furthermore, the semantics available to the runtime are lost at the system-call boundary in such OSes. Finally, because a runtime executes at user- level in such an environment, it cannot leverage hardware features that require kernel-mode privileges—a large portion of the functionality of the machine is lost to it. These limita- tions warp the design, implementation, functionality, and performance of parallel runtimes. I make the case for eliminating these compromises by transforming parallel runtimes into This work was made possible by support from the United States National Science Foundation through grants CCF-1533560 and CNS-0709168, from the United States Department of Energy through grant number DE- SC0005343, and from Sandia National Laboratories through the Hobbes Project, which is funded by the 2013 Exascale Operating and Runtime Systems Program under the Office of Advanced Scientific Computing Research in the DoE’s Office of Science. hybrid runtimes (HRTs), runtimes that run as kernels, and that enjoy full hardware access and control over abstractions to the machine. The primary claim of this dissertation is that the hybrid runtime model can provide significant benefits to parallel runtimes and the applications that run on top of them. -
Getting Started with XL Fortran
IBM XL Fortran for Blue Gene/Q, V14.1 Getting Started with XL Fortran Ve r s i o n 1 4 .1 GC14-7366-00 IBM XL Fortran for Blue Gene/Q, V14.1 Getting Started with XL Fortran Ve r s i o n 1 4 .1 GC14-7366-00 Note Before using this information and the product it supports, read the information in “Notices” on page 31. First edition This edition applies to IBM XL Fortran for Blue Gene/Q, V14.1 (Program 5799-AH1) and to all subsequent releases and modifications until otherwise indicated in new editions. Make sure you are using the correct edition for the level of the product. © Copyright IBM Corporation 1996, 2012. US Government Users Restricted Rights – Use, duplication or disclosure restricted by GSA ADP Schedule Contract with IBM Corp. Contents About this document .........v Language support enhancements .......12 Conventions ..............v Fortran 2008 features ..........12 Related information ............ix Other XL Fortran language-related updates . 15 IBM XL Fortran information ........ix OpenMP 3.1 .............16 Standards and specifications ........x Performance and optimization ........16 Other IBM information..........xi New diagnostic reports ..........17 Technical support ............xi How to send your comments ........xi Chapter 3. Setting up and customizing XL Fortran .............21 Chapter 1. Introducing XL Fortran . 1 Using custom compiler configuration files ....21 About the Blue Gene architecture .......1 Commonality with other IBM compilers .....1 Chapter 4. Developing applications Operating system support ..........2 -
Designing OS for HPC Applications: Scheduling
2010 IEEE International Conference on Cluster Computing Designing OS for HPC Applications: Scheduling Roberto Gioiosa∗, Sally A. McKeey, Mateo Valero∗z ∗Computer Science Division Barcelona Supercomputing Center, ES yComputer Science and Engineering Chalmers University of Technology, SE zComputer Architecture Department Universitat Politecnica de Catalunya, ES [email protected], [email protected], [email protected] Abstract—Operating systems have historically been implemented provides portability and transparency, but may not provide as independent layers between hardware and applications. User optimal performance. programs communicate with the OS through a set of well Modern Chip Multi-Processors (CMPs) share different levels defined system calls, and do not have direct access to the of internal hardware resources among cores and hardware hardware. The OS, in turn, communicates with the underlying architecture via control registers. Except for these interfaces, threads, from the internal pipeline, to the caches, down to the the three layers are practically oblivious to each other. While memory controllers. Single thread performance is no longer this structure improves portability and transparency, it may not improving, and applications must exploit more parallelism for deliver optimal performance. This is especially true for High overall system throughput. This is especially true for High Performance Computing (HPC) systems, where modern parallel Performance Computing (HPC) systems where modern paral- applications and multi-core architectures pose new challenges in terms of performance, power consumption, and system utiliza- lel applications and CMP architectures pose new challenges tion. The hardware, the OS, and the applications can no longer for performance, power consumption, and system utilization. remain isolated, and instead should cooperate to deliver high HPC applications have long been parallel (usually using MPI performance with minimal power consumption. -
Getting Started with XL C/C++
IBM XL C/C++ for Blue Gene/Q, V12.1 Getting Started with XL C/C++ Ve r s i o n 12 .1 GC14-7361-00 IBM XL C/C++ for Blue Gene/Q, V12.1 Getting Started with XL C/C++ Ve r s i o n 12 .1 GC14-7361-00 Note Before using this information and the product it supports, read the information in “Notices” on page 37. First edition This edition applies to IBM XL C/C++ for Blue Gene/Q, V12.1 (Program 5799-AG1) and to all subsequent releases and modifications until otherwise indicated in new editions. Make sure you are using the correct edition for the level of the product. © Copyright IBM Corporation 1996, 2012. US Government Users Restricted Rights – Use, duplication or disclosure restricted by GSA ADP Schedule Contract with IBM Corp. Contents About this document .........v Other new or changed compiler options and Conventions ..............v pragma directives ...........12 Related information ............ix Language support enhancements .......16 IBM XL C/C++ information ........ix C++0x features ............16 Standards and specifications ........x C1X features .............22 Other IBM information..........xi OpenMP 3.1 .............23 Other information ...........xi New built-in functions..........24 Technical support ............xi Performance and optimization ........24 How to send your comments ........xi New diagnostic reports ..........25 Chapter 1. Introducing XL C/C++ ....1 Chapter 3. Setting up and customizing About the Blue Gene architecture .......1 XL C/C++..............29 Commonality with other IBM compilers .....1 Using custom compiler configuration files ....29 Operating system support ..........2 A highly configurable compiler ........2 Chapter 4.