Multiprocessing

Résumé

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, mostly as a function of how CPUs are defined (multiple cores on one die, multiple dies in one package, multiple packages in one system unit, etc.). According to some on-line dictionaries, a multiprocessor is a computer system having two or more processing units (multiple processors) each sharing main memory and peripherals, in order to simultaneously process programs. A 2009 textbook defined multiprocessor system similarly, but noting that the processors may share "some or all of the system’s memory and I/O facilities"; it also gave tightly coupled system as a synonymous term. At the operating system level, multipr

Source officielle

https://en.wikipedia.org/wiki/Multiprocessing

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Multiprocessors are a core component in all types of computing infrastructure, from phones to datacenters. This course will build on the prerequisites of processor design and concurrency to introduce the essential technologies required to combine multiple processing elements into a single computer.

Hardware compilation is the process of transforming specialized hardware description languages into circuit descriptions, which are iteratively refined, detailed and optimized. The course presents algorithms, tools and methods for hardware compilation and logic synthesis.

With the advent of multiprocessors, it becomes crucial to master the underlying algorithmics of concurrency. The objective of this course is to study the foundations of concurrent algorithms and in particular the techniques that enable the construction of robust such algorithms.

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Load Sharing for Multiprocessor Network Nodes

This thesis discusses techniques for sharing the processing load among multiple processing units within systems that act as nodes in a data communications network. Load-sharing techniques have been explored in the field of computer science for many years and their beneits are well known, including better utilization of processing capacity and enhanced system fault tolerance. We discuss deploying such methods in the specifics of the networking environment. We concentrate particularly on the data plane, or the data packet-processing tasks. After reviewing the main results in the fields of load sharing and multiprocessor networking systems architectures, we conduct a preparatory optimization study of a router system to gain better understanding of the optimization issues in a particular multiprocessor system. The main contribution of this thesis, the adaptive load-sharing method, is presented next. We first formulate the optimization problem of mapping packets to processors. The goal is to minimize the likelihood of flow reordering, while respecting certain system constraints, such as the acceptable probability of a packet loss. As we show that the task is an NP-complete problem, we propose a heuristic method that uses an adaptive hash-based mapping to assign packets to processors. We demonstrate its advantages and prove that the method adaptation policy possesses the key minimal disruption property with respect to the mapping. In other words, the adaptation results in a minimum number of ows being moved among processing units. Further on, the method is validated in an extensive set of simulations designed to imitate the networking environment. Finally, two sample applications, an architecture of a multiprotocol router and an implementation of a server load balancer on a network processor demonstrate the applicability of the method.

2003

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Load sharing for multiprocessor network nodes

This thesis discusses techniques for sharing the processing load among multiple processing units within systems that act as nodes in a data communications network. Load-sharing techniques have been explored in the field of computer science for many years and their benefits are well known, including better utilization of processing capacity and enhanced system fault tolerance. We discuss deploying such methods in the specifics of the networking environment. We concentrate particularly on the data plane, or the data packet-processing tasks. After reviewing the main results in the fields of load sharing and multiprocessor networking systems architectures, we conduct a preparatory optimization study of a router system to gain better understanding of the optimization issues in a particular multiprocessor system. The main contribution of this thesis, the adaptive load-sharing method, is presented next. We first formulate the optimization problem of mapping packets to processors. The goal is to minimize the likelihood of flow reordering, while respecting certain system constraints, such as the acceptable probability of a packet loss. As we show that the task is an NP-complete problem, we propose a heuristic method that uses an adaptive hash-based mapping to assign packets to processors. We demonstrate its advantages and prove that the method adaptation policy possesses the key minimal disruption property with respect to the mapping. In other words, the adaptation results in a minimum number of flows being moved among processing units. Further on, the method is validated in an extensive set of simulations designed to imitate the networking environment. Finally, two sample applications, an architecture of a multiprotocol router and an implementation of a server load balancer on a network processor demonstrate the applicability of the method.

EPFL2003

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JErlang: Erlang with Joins

Hubert Plociniczak

ERLANG is an industrially successful functional language that uses the Actor model for concurrency. It supports the message-passing paradigm by providing pattern-matching over received messages. Unfortunately coding synchronisation between multiple processes is not straightforward. To overcome this limitation we designed and implemented JERLANG, a JOIN-CALCULUS inspired extension to ERLANG. We provide a rich set of language features with our joins. We present implementation details of our two alternative solutions, a library and an altered VM. Our optimisations provide JERLANG with good performance.

Springer-Verlag New York, Ms Ingrid Cunningham, 175 Fifth Ave, New York, Ny 10010 Usa2010

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