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Tuesday, May 5, 2020 | History

4 edition of Processor scheduling in hierarchical NUMA multiprocessors found in the catalog.

Processor scheduling in hierarchical NUMA multiprocessors

Nandini Srikantiah

Processor scheduling in hierarchical NUMA multiprocessors

by Nandini Srikantiah

  • 245 Want to read
  • 39 Currently reading

Published by National Library of Canada = Bibliothèque nationale du Canada in Ottawa .
Written in English


Edition Notes

SeriesCanadian theses = Thèses canadiennes
The Physical Object
FormatMicroform
Pagination1 microfiche : negative.
ID Numbers
Open LibraryOL14712537M
ISBN 100315743263
OCLC/WorldCa30072505

A multi-core processor is a computer processor integrated circuit with two or more separate processing units, called cores, each of which reads and executes program instructions, as if the computer had several processors. The instructions are ordinary CPU instructions (such as add, move data, and branch) but the single processor can run instructions on separate cores at the same time. the simplest are the so-called NUMA (non-uniform memory access) multiprocessors. Mod-ern NUMA machines have caches, but the hardware does nothing to keep those caches consistent. Examples of NUMA machines include the BBN TC, the Hector machine at the University of Toronto [73], the Cray Research T3D, and the forthcoming Shrimp machine [12].

Welcome to the proceedings of the International Symposium on Parallel and Distributed Processing and Applications (ISPA ) which was held in Aizu-Wakamatsu City, Japan, July 2–4, Parallel and distributed processing has become a key technology which will play an important part in determining, or at least shaping, future research. @article{osti_, title = {Issues of locality in a distributed virtual memory}, author = {Marinelli, R.J.}, abstractNote = {A distributed virtual memory operating system for a hierarchical local/shared memory architecture multiprocessor is described. A working prototype system, CPK/MP, has been implemented on an eight processor RISC personal multiprocessor.

Hierarchical Scheduling in Parallel and Cluster Systems 英文书摘要. Multiple processor systems are an important class of Parallel systems. Over the years, several architectures have been proposed to build such systems to satisfy the requirements of high performance computing. These architectures span a wide variety of system types. 14 CHAPTER 2. EVOLVING TOWARDS CC-NUMA MULTIPROCESSORS processors. Each processor holds only a portion of the total system memory. If a processor needs to access remote data, it must send a message to the remote node. Hence, this ar-chitecture is called message passing because every node must explicitly communicate with another node using a.


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Processor scheduling in hierarchical NUMA multiprocessors by Nandini Srikantiah Download PDF EPUB FB2

Abstract. In this paper we describe the design, implementation and experimental evaluation of a technique for operating system schedulers called processor pool-based scheduling [51]. Our technique is designed to assign processes (or kernel threads) of parallel applications to processors in multiprogrammed, shared-memory NUMA by: The HWLOC library is used to perform the topology discovery which builds a hierarchical architecture composed of hardware objects (NUMA nodes, sockets, caches, cores, etc.), and the BubbleSched.

For Non-Uniform Memory Access (NUMA) multiprocessors, memory access overhead is crucial to system performance. Processor scheduling and page placement schemes, dominant factors of. A multiprocessor system is an interconnection of two or more CPUs with memory and input- output equipment.

The term "processor" in multiprocessor can mean either a central processing unit (CPU) or. These systems, for example, use a multistage dynamic interconnection network.

Such systems also provide global, shared memory like the UMA systems. However, they introduce local and remote memories, which lead to non-uniform memory access (NUMA) architecture. Distributed-memory architecture is used for systems with thousands of pro­ cessors. Hierarchical Scheduling in Parallel and Cluster Systems.

Authors: Dandamudi, Sivarama shared memory like the UMA systems. However, they introduce local and remote memories, which lead to non-uniform memory access (NUMA) architecture.

Scheduling in Shared-Memory Multiprocessors. Note: If you're looking for a free download links of Hierarchical Scheduling in Parallel and Cluster Systems (Series in Computer Science) Pdf, epub, docx and torrent then this site is not for you.

only do ebook promotions online and we does not. These systems, for example, use a multistage dynamic interconnection network. Such systems also provide global, shared memory like the UMA systems. However, they introduce local and remote memories, which lead to non-uniform memory access (NUMA) architecture.

Distributed-memory architecture is used for systems with thousands of pro­ cturer: Springer. Hierarchical Scheduling in Parallel and Cluster Systems (Series in Computer Science) Pdf, Download Ebookee Alternative Reliable Tips For A Better Ebook Reading Experience.

master processor. Scheduling for Processor A nity. Schedulers on NUMA machines should almost certainly maintain an a nity between processors and the pro-cesses that run on them because of the large amounts of process state that reside near the processors.

Even on traditional UMA (uniform memory access) multiproces-Cited by: ELSEVIER Performance Evaluation 19 () PERFORMANCE EVALUATION An International Journal Invited paper Application scheduling and processor allocation in multiprogrammed parallel processing systems K.C. Sevcik Computer Systems Research Institute, University of Toronto, 10 King's College Road, Toronto, Ont.

Canada M5S 1A4 Abstract When large-scale multiprocessors for parallel Cited by: The book presents two approaches to automatic partitioning and scheduling so that the same parallel program can be made to execute efficiently on widely different multiprocessors.

The first approach is based on a macro dataflow model in which the program is partitioned into tasks at compile time and the tasks are scheduled on processors at run. The problem of nonpreemptively scheduling a set of m partially ordered tasks on n identical processors subject to interprocessor communication delays is studied in an effort to minimize the makespan.

A new heuristic, called Earliest Task First (ETF), is designed and analyzed. It is shown that the makespan $\omega _{{\text{ETF}}} $ generated by ETF always satisfies $\omega _{{\text{ETF}}} \leqq Cited by: Multiprocessing is the use of two or more central processing units (CPUs) within a single computer system.

The term also refers to the ability of a system to support more than one processor or the ability to allocate tasks between them. There are many variations on this basic theme, and the definition of multiprocessing can vary with context. However, access to memory attached to a remote processor is slower (has higher latency and also typically reduced bandwidth) than access to a local memory.

This results in non-uniform memory access (NUMA). Ideally, threads should be placed on cores. multiprocessors and multicomputers 1. Multiprocessors and Multicomputers 2.

Categories of Parallel Computers Considering their architecture only, there are two main categories of parallel computers: systems with shared common memories, and systems with unshared distributed memories.

Welcome to the proceedings of the International Symposium on Parallel and Distributed Processing and Applications (ISPA ) which was held in Aizu-Wakamatsu City, Japan, July 2–4, Parallel and distributed processing has become a key technology which will play an important part in.

Multithreaded Processor 49 3 Parallel Computers 53 Introduction 53 Parallel Computing 53 Shared-Memory Multiprocessors (Uniform Memory Access [UMA]) 54 Distributed-Memory Multiprocessor (Nonuniform Memory Access [NUMA]) 56 viiFile Size: 8MB.

Lai G, Fang J, Sung P and Pean D Scheduling parallel tasks onto NUMA multiprocessors with inter-processor communication overhead Proceedings of the international conference on Parallel and distributed processing and applications, ().

The holistic model (a) is based on template-based code\ud generation for each executed query, (b) uses multithreading to adapt to multicore processor\ud architectures and (c) addresses the optimization problem of scheduling multiple\ud threads for intra-query parallelism.\ud Main-memory query execution is a usual operation in modern database Author: Konstantinos Krikellas.

As distributed computer systems become more pervasive, so does the need for understanding how their operating systems are designed and implemented. Andrew S. Tanenbaum`s Distributed Operating Systems fulfills this need.

Representing a revised and greatly expanded Part II of the best-selling Modern Operating Systems, it covers the material from the original book, including communication /5().A simple and efficient method for evaluating the performance of an algorithm, rendered as a directed acyclic graph, on any parallel computer is presented.

The crucial ingredient is an efficient approximation algorithm for a particular scheduling problem. The only parameter of the parallel computer needed by our method is the message-to-instruction ratio $\tau$.Cited by: There is a software gap between the hardware potential and the performance that can be attained using today's software parallel program development tools.

The tools need manual intervention by the - Selection from Algorithms and Parallel Computing [Book].