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About 2,110 papers for “processor allocation”

Processor Allocation on Cplant: Achieving General Processor Locality Using One-Dimensional Allocation Strategies

Vitus J. Leung, Esther M. Arkin, Michael A. Bender et al. · OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · 2002

The Computational Plant, or Cplant is a commodity-based supercomputer under development at Sandia National Laboratories. This paper describes resource-allocation strategies to achieve processor locality for parallel jobs in Cplant and other supercomputers. Users of Cplant and other Sandia supercomputers submit parallel jobs to a job queue. When a job is scheduled to run, it is assigned to a set of processors. To obtain maximum throughput, jobs should be allocated to localized clusters of processors to minimize communication costs and to avoid bandwidth contention caused by overlapping jobs. This paper introduces new allocation strategies and performance metrics based on space-tilling curves and one dimensional allocation strategies. These algorithms are general and simple. Preliminary simulations and Cplant experiments indicate that both space-filling curves and one-dimensional packing improve processor locality compared to the sorted free list strategy previously used on Cplant. These new allocation strategies are implemented in the new release of the Cplant System Software, Version 2.0, phased into the Cplant systems at Sandia by May 2002.

Cited by 34Open access

Processor allocation on Cplant: achieving general processor locality using one-dimensional allocation strategies

Vitus J. Leung, Esther M. Arkin, Ma. Bender et al. · 2003

The Computational Plant or Cplant is a commodity-based supercomputer under development at Sandia National Laboratories. This paper describes resource-allocation strategies to achieve processor locality for parallel jobs in Cplant and other supercomputers. Users of Cplant and other Sandia supercomputers submit parallel jobs to a job queue. When a job is scheduled to run, it is assigned to a set of processors. To obtain maximum throughput, jobs should be allocated to localized clusters of processors to minimize communication costs and to avoid bandwidth contention caused by overlapping jobs. This paper introduces new allocation strategies and performance metrics based on space-filling curves and one dimensional allocation strategies. These algorithms are general and simple. Preliminary simulations and Cplant experiments indicate that both space-filling curves and one-dimensional packing improve processor locality compared to the sorted free list strategy previously used on Cplant. These new allocation strategies are implemented in the new release of the Cplant System Software, Version 2.0, phased into the Cplant systems at Sandia by May 2002.

Cited by 48

II. Processor Allocation Strategies.......................................................................................................................... 2

Avanti Nadgir, Harshal Haridas · 2008

The ordering of operations in a data flow program is not specified by the programmer, but is implied by the data dependencies. This advantage can be exploited further on multiprocessor architectures by grouping the nodes in the corresponding data flow graph and allocating these groups efficiently to processors. This paper presents and compares some of the numerous heuristic approaches that were proposed to partition data flow graphs and assign them to different processors. The processor allocation algorithms, which do not consider the communication cost between processors, are presented initially. A Region analysis algorithm that enables better load balancing but again does not consider communication cost is presented. Schauser et. al. developed an intermediate data structure “dual graph ” to transition a data flow graph into threads which easily compiled and mapped on Threaded Abstract Machine. Lastly, algorithms, which consider these costs, are studied. We present a design pattern that can be summarized from these algorithms to efficiently partition data flow graphs. We also list the key issues that need to be addressed during data flow partitioning.

Cited by 0

Processor allocation in hypercube multiprocessors

S. Rai, Jerry L. Trahan, Thomas Smailus · IEEE Transactions on Parallel and Distributed Systems · 1995

The processor allocation problem requires recognizing and locating a free subcube that can accommodate a request for a subcube of a specified size for an incoming task. Methods reported in the literature fall into two strategies: bottom-up or bit mapped technique (BMT) and top-downer available cube technique (ACT). Our algorithm that solves the allocation problem in faulty hypercubes falls into the category of ACT's which offer the advantage over BMT's of quickly recognizing whether or not a requested subcube is available in the list of fault-free subcubes. We introduce new algebraic functions and the concept of separation factor to select a subcube for allocation. The notion of overlap-syndrome, defined in the text, quantifies the overlap among free subcubes. Our technique has full subcube recognition ability and thus recognizes more subcubes as compared to bit mapped techniques: Buddy, Gray code and its variants. The advantages of our approach over some of the existing ACT's in terms of fragmentation and overall completion time are described in the text and in simulation results.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Cited by 11

Processor Allocation, Message Scheduling, and

Algorithm Selection For, Jack M. West · 2007

VI TABLES ...............................................................................................................................VIII FIGURES .................................................................................................................................X CHAPTER I ..............................................................................................................................1

Cited by 0

Distributed Processor Allocation in Multicomputers

Cesar Augusto Fonticielha De Rose, Hans Ulrich Heiss, Philippe Olivier Alexander Navaux · PUCRS Repository (Pontifical Catholic University of Rio Grande do Sul) · 2000

Current processor allocation techniques for multicomputers are based on centralized front-end based algorithms. As a result, the applied strategies are usually restricted to static, contiguous, structure preserving allocation, and suffer from low parallelism and weak fault tolerance. To lift these restrictions we are investigating a distributed approach to the processor allocation problem for mesh interconnected distributed memory machines. We conducted several experiments, some simulated and some running over a Simens hpcLine Primergy Server with 96 nodes, which showed that distributed allocation is feasible with current technologies.

Cited by 0Open access

Processor Allocation and Scheduling in

Distributed Systems Mohankumar, Mohankumar Zade, Nihal Ch et al. · 2007

this paper. This section also comments on the difference between the terms processor allocation and scheduling in context of distribute systems. Section III attempts to categorize the algorithms proposed in various categories for better understanding, comparison and future works. In section IV some example algorithms are discussed and section V briefly describes some example processor allocation algorithms of various classes. section VI presents co-scheduling algorithm. Lastly, summary and conclusions are presented in section VII

Cited by 0

Processor allocation in parallel battlefield simulation

Narsingh Deo, Muralidhar Medidi, Sushil K. Prasad · Journal of International Crisis and Risk Communication Research · 1992

Load balancing is a critical issue for exploiting the parallelism in any application and, particularly, in battlefield simulation where the computational load dynamically changes with both time and space. Domain decomposition is an effective means to balance the load distribution in battlefield simulation. However, finer domain decompositions that lead to better load balance incur heavier communication overhead. Earlier attempts in parallelizing battlefield sinlulation have traded load balance in favor of low con~-munication overhead. In this paper, we present three parallel battlefield simulators, implemented on Intel's iPSC/2 and BBN Butterfly GP-1OOO multicomputers, with finer domain decomposition and address the communication overhead problem by processor allocation strategies that suit the underlying architecture of the machine, On the shared-memory BBN Butterfly, the strategy leads to a new parallel battlefield simulation with dynamic load balancing. Execution times of these simulators are provided, which show that the communication overhead is tolerable.

Cited by 7Open access

Processor Allocation in Tightly Coupled Multiprocessors

Patricie Kostková · 1995

Contents 1 Introduction 7 1.1 Motivations of Distributed Systems : : : : : : : : : : : : : : : : : 8 1.1.1 Advantages of Distributed Systems : : : : : : : : : : : : : 8 1.1.2 Disadvantages of Distributed Systems : : : : : : : : : : : 8 1.2 Hardware in Distributed Systems : : : : : : : : : : : : : : : : : : 9 1.3 Software in Distributed Systems : : : : : : : : : : : : : : : : : : 10 1.3.1 Software Concepts : : : : : : : : : : : : : : : : : : : : : : 11 1.3.1.1 Loosely Coupled Software : : : : : : : : : : : : : 11 1.3.1.2 Tightly Coupled Software : : : : : : : : : : : : : 11 1.3.2 Design Issues for Distributed Operating Systems : : : : : 12 1.3.3 Microkernel Concept versus Monolitic Kernel Concept : : 13 1.4 Introduction into Processor Allocation : : : : : : : : : : : : : : : 13 1.4.1 Allocation Str

Cited by 0

Dynamic processor allocation in hypercube computers

Po‐Jen Chuang, Nian-Feng Tzeng · 1990

Fully recognizing various subcubes in a hypercube computer efficiently is nontrivial due to the specific structure of the hypercube. We propose a method with much less complexity than the multiple-GC strategy in generating the search space, while achieving complete subcube recognition. This method is referred to as a dynamic processor allocation scheme because the search space generated is dependent upon the dimension of the requested subcube dynamically, rather than being predetermined and fixed. The basic idea of this strategy lies in collapsing the binary tree representations of a hypercube successively so that the nodes which form a subcube but are distant would be brought close to each other for recognition. The strategy can be implemented efficiently by using shuffle operations on the leaf node addresses of binary tree representations. Extensive simulation runs are carried out to collect experimental performance measures of interest of different allocation strategies. It is shown from analytic and experimental results that this strategy compares favorably in many situations to any other known allocation scheme capable of achieving complete subcube recognition.

Cited by 0

Register allocation for Intel processor graphics

Wei-Yu Chen, Guei-Yuan Lueh, Pratik Ashar et al. · 2018

Register allocation is a well-studied problem, but surprisingly little work has been published on assigning registers for GPU architectures. In this paper we present the register allocator in the production compiler for Intel HD and Iris Graphics. Intel GPUs feature a large byte-addressable register file organized into banks, an expressive instruction set that supports variable SIMD-sizes and divergent control flow, and high spill overhead due to relatively long memory latencies. These distinctive characteristics impose challenges for register allocation, as input programs may have arbitrarily-sized variables, partial updates, and complex control flow. Not only should the allocator make a program spill-free, but it must also reduce the number of register bank conflicts and anti-dependencies. Since compilation occurs in a JIT environment, the allocator also needs to incur little overhead.

Cited by 4

Processor bit allocation of the example.

Sulan Zhang (15426667), Junwei Chen (518407), Zihao Liu (4020458) et al. · Figshare · 2023

&lt;div&gt;&lt;p&gt;Ternary Optical Computer (TOC) is more advanced than traditional computer systems in parallel computing, which is characterized by huge amounts of repeated computations. However, the application of the TOC is still limited because of lack of key theories and technologies. In order to make the TOC applicable and advantageous, this paper systematically elaborates the key theories and technologies of parallel computing for the TOC through a programming platform, including reconfigurability and groupable usability of optical processor bits, parallel carry-free optical adder and the TOC’s application characteristics, communication file to express user’s needs and data organization method of the TOC. Finally, experiments are carried out to show the effectiveness of the present theories and technologies for parallel computing, as well as the feasibility of the implementation method of the programming platform. For a special instance, it is shown that the clock cycle on the TOC is only 0.26% of on a traditional computer, and the computing resource spent on the TOC is 25% of that on a traditional computer. Based on the study of the TOC in this paper, more complex parallel computing can be realized in the future.&lt;/p&gt;&lt;/div&gt;

Cited by 0Open access

Dynamic processor allocation in hypercube computers

Po‐Jen Chuang, Nian-Feng Tzeng · ACM SIGARCH Computer Architecture News · 1990

Fully recognizing various subcubes in a hypercube computer efficiently is nontrivial due to the specific structure of the hypercube. We propose a method with much less complexity than the multiple-GC strategy in generating the search space, while achieving complete subcube recognition. This method is referred to as a dynamic processor allocation scheme because the search space generated is dependent upon the dimension of the requested subcube dynamically, rather than being predetermined and fixed. The basic idea of this strategy lies in collapsing the binary tree representations of a hypercube successively so that the nodes which form a subcube but are distant would be brought close to each other for recognition. The strategy can be implemented efficiently by using shuffle operations on the leaf node addresses of binary tree representations. Extensive simulation runs are carried out to collect experimental performance measures of interest of different allocation strategies. It is shown from analytic and experimental results that this strategy compares favorably in many situations to any other known allocation scheme capable of achieving complete subcube recognition.

Cited by 20Open access

Processor allocation in faulty hypercube multiprocessors

S. Rai, Jerry L. Trahan, Thomas Smailus · 1993 IEEE International Symposium on Circuits and Systems · 2002

The processor allocation problem in hypercubes is to recognize and locate a free subcube that can accommodate a request for a subcube of a specified size for an incoming task. A new approach for this processor allocation problem in faulty hypercubes is presented. A new concept is introduced, i.e., the growth factor, to select a subcube for allocation, which in turn utilizes the notion of overlap-syndrome to quantify the overlap among free subcubes. The authors' technique has full subcube recognition ability and thus recognizes more subcubes as compared to buddy, Gray code and its variants. The advantages of their approach over some existing approaches are described.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Cited by 0

Resource Allocation Policies for Multithreading Processor

Biao Wang · 2008

The problem of how to allocate and share processor resources among multiple threads of multithreading processors has a direct effect on the performance of the processor.Four allocation models and the mechanism for implementation are brought out in this paper,and the balance of resource allocation is discussed.It points out that different allocation models and implementation mechanisms can be applied to different pipeline stage according to such factors as the character of the object application and pipeline stage,and so on,to allocate the processor resources reasonably.

Cited by 0