MULTI-CORE ARCHITECTURES AND PROGRAMMING (original) (raw)
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Multi- and Many-Cores, Architectural Overview for Programmers
2017
Parallelism has been used since the early days of computing to enhance performance. From the first computers to the most modern sequential processors (also called uniprocessors), the main concepts introduced by von Neumann [20] are still in use. However, the ever-increasing demand for computing performance has pushed computer architects toward implementing different techniques of parallelism. The von Neumann architecture was initially a sequential machine operating on scalar data with bit-serial operations [20]. Word-parallel operations were made possible by using more complex logic that could perform binary operations in parallel on all the bits in a computer word, and it was just the start of an adventure of innovations in parallel computer architectures.
Multi-Core Programming Performance and Analyzes
international journal of research in computer application & management, 2013
The research intended to find performance issue on the architecture hardware as well as software prospective boosting up the processors speed is only not the issues but Speedup has been achieved by increasing clock speeds and, more recently, adding multiple processing cores to the same chip. The major Processor manufacturer from Intel , AMD & All leading Processor Manufacturer are boosting CPU Performance from last 20 years to till Date how the change take place not only in processor but also in software development the turning point it seem changing face of hardware too. It suddenly does matter to software, the concurrency revolution will also change the way of writing software in the future. The revolution in software development from structured programming to object oriented Programming is change in the past 30 years. The people are doing Object oriented Programming in simula, JAVA to solve larger Problems for Larger system and writing the program for economical, reliable and repeatable. Using Multi-core architecture and making Multi-core Programming (Parallel Programming) which we can make the difference in sequential as well as parallel programming.
2010
This paper is motivated by the desire to provide an efficient and scalable software cache implementation of OpenMP on multicore and manycore architectures in general, and on the IBM CELL architecture in particular. In this paper, we propose an instantiation of the OpenMP memory model with the following advantages: (1) The proposed instantiation prohibits undefined values that may cause problems of safety, security, programming and debugging. (2) The proposed instantiation is scalable with respect to the number of threads because it does not rely on communication among threads or a centralized directory that maintains consistency of multiple copies of each shared variable. (3) The proposed instantiation avoids the ambiguity of the original memory model definition proposed on the OpenMP Specification 3.0. We also introduce a new cache protocol for this instantiation, which can be implemented as a software-controlled cache. Experimental results on the Cell Broadband Engine show that our instantiation results in nearly linear speedup with respect to the number of threads for a number of NAS Parallel Benchmarks. The results also show a clear advantage when comparing it to a software cache design derived from a stronger memory model that maintains a global total ordering among flush operations.
Comparative Study of Multi-Threading Libraries to Fully Utilize Multi Processor/Multi Core Systems
The development of multi-core technology has led to a great shift from sequential programming to parallel programming. This has made substantial challenges to software industries and government organizations to take full advantage of the performance intensification offered by the multi core systems. This paper aspires to compare and analyze the parallel computing ability offered by OpenMP(Open Multiprocessing), Intel Cilk Plus and MPI(Message passing Interface). Some proposals are also provided in parallel programming. The parallel programming features provided by these libraries are also studied and compared. The study is done by parallelizing problems related to Remote Sensing data processing which is large in volume and whose sequential processing is very much time consuming. This makes it pertinent to speed up the processing times by introducing parallelism in processing and for efficient utilization of multi processor multi core systems. The paper aims at exploring these libraries and studying the speed up achieved by using parallel processing and Data Parallelism paradigm.
Structuring the execution of OpenMP applications for multicore architectures
2010 IEEE International Symposium on Parallel & Distributed Processing (IPDPS), 2010
The now commonplace multi-core chips have introduced, by design, a deep hierarchy of memory and cache banks within parallel computers as a tradeoff between the user friendliness of shared memory on the one side, and memory access scalability and efficiency on the other side. However, to get high performance out of such machines requires a dynamic mapping of application tasks and data onto the underlying architecture. Moreover, depending on the application behavior, this mapping should favor cache affinity, memory bandwidth, computation synchrony, or a combination of these. The great challenge is then to perform this hardware-dependent mapping in a portable, abstract way.
Computer Organization and Architecture Chapter 8 : Multiprocessors Compiled By: Er. Hari Aryal
Characteristics of multiprocessors 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 an input-output processor (IOP). Multiprocessors are classified as multiple instruction stream, multiple data stream (MIMD) systems The similarity and distinction between multiprocessor and multicomputer are o Similarity Both support concurrent operations o Distinction The network consists of several autonomous computers that may or may not communicate with each other. A multiprocessor system is controlled by one operating system that provides interaction between processors and all the components of the system cooperate in the solution of a problem. Multiprocessing improves the reliability of the system. The benefit derived from a multiprocessor organization is an improved system performance.
Efficient Programming Model for OpenMP on Cluster-Based Many-Core System
2015
Da die Komplexität "System-on-Chip" (SoC) auch weiterhin zunimmt, wird man die Herausforderungen aufgrund der Konvergenz der Software- und Hardwareentwicklung nicht ignorieren können. Dies gilt auch für den Umgang mit dem hierarchischen Design, in dem die Prozessorkerne in Clustern oder sogenannten "Tiles" angeordnet werden, um mittels eines schnellen lokalen Speicherzugriffs eine geringe Latenz und eine hohe Bandbreite der lokalen Kommunikation zu gewährleisten. Aus der Sicht eines Programmierers ist es wünschenswert, sich diese Eigenheiten der Hardware zunutze zu machen und sie bei der Ausgestaltung der abstrakten Parallel-Programmierung gewissenhaft und zielführend zu berücksichtigen. Diese Dissertation überwindet viele Engpässe in Bezug auf die Skalierbarkeit Cluster-basierter Many-Core-Systeme und führt das Programmiermodell OpenMP zur Vereinfachung der Anwendungsentwicklung ein. OpenMP abstrahiert von der Sichtweise des Programmierers – und es werden Richtl...
An Implementation and Evaluation of Thread Subteam for OpenMP Extensions
OpenMP provides a portable programming interface on shared memory multiprocessors (SMPs). The set of features in the current OpenMP specification provides essential functionality that was selected mostly from existing shared-memory parallel application programming interfaces (APIs). Although this interface has proven successful for small SMPs, it requires greater flexibility in light of the steadily growing size of individual SMPs and the recent advent of multithreaded chips. In this paper, we introduce the syntax and semantics of a proposed OpenMP extension for facilitating the expression of worksharing on the emerging chip multithreading architectures. We also describe our implementation in the OpenUH reference OpenMP compiler and the runtime library. We then evaluate the new feature using a kernel of seismic data processing application.