Processor Allocation Strategy Research Articles

Three Processor Allocation Approaches towards EDF Scheduling for Performance Asymmetric Multiprocessors

With the rapid development of high-performance computing and parallel computing technology, by virtue of its cost-effectiveness, strong scalability, and easy programming, the multiprocessor system has gradually become the mainstream computing platform. Meanwhile, a growing number of researchers pay attention to the performance of multiprocessor systems, especially the task scheduling problem, which has an important impact on the system performance. Most of the current research works on task scheduling algorithms are based on the homogeneous computing environment. On the contrary, research works focusing on more complex performance asymmetric multiprocessor environments still remain rare. In this paper, we compare the effects of three earliest deadline first algorithms under different processor allocation strategies on performance asymmetric multiprocessors. We propose an efficient schedulability analysis for an allocation strategy that assigns high-priority tasks to the slowest idle processor. Experimental results show that the strategy of allocating processors with optimum speeds for high-priority tasks can schedule more task sets than the other two allocation strategies. The strategy that prioritizes the slowest processors for high-priority tasks has the smallest number of task migrations, and the strategy has the highest effective processor utilization.

Improving system performance in non-contiguous processor allocation for mesh interconnection networks

Contiguous allocation of parallel jobs in multicomputers usually suffers from the degrading effects of fragmentation, because it requires that the allocated processors be contiguous and have the same topology as that of the multicomputer's interconnection network. Fragmentation can be avoided by adopting non-contiguous allocation. However, non-contiguous allocation can increase the distances among processors allocated to a job, which can increase the interference among messages of different jobs and increases message contention and delays. This paper suggests a new non-contiguous processor allocation strategy, referred to as Minimum Interference Paging (MIP), for the 2D mesh network. MIP attempts to reduce the distances among processors allocated using a paging variant that chooses a set of processors with the lowest distance between the first and last allocated processors, where the distance is the number of processors between the first allocated node and last allocated node. Using software simulation, we compared the performance of MIP against that of several well-known non-contiguous allocation strategies: paging (0), Multiple Buddy System (MBS) and Adaptive Non-contiguous Allocation (ANCA). The comparative evaluation was conducted using First-Come-First-Served (FCFS) job scheduling, wormhole routing and six communication patterns. These are the one-to-all, all-to-all, Near Neighbour, Ring, Divide and Conquer Binomial Tree (DQBT), and Random communication patterns. The results show that MIP exhibits superior performance in terms of average turnaround time of jobs.

Shape-and Orientation-independent 2D-Buddy Processor Allocation Strategy in 2-D Mesh-based Multicomputers

We propose and evaluate a new processor allocation strategy in two-dimensional Multicomputers. The proposed strategy is comparatively evaluated against a set of well-known allocation strategies from the literature, namely; the 2D buddy System (Juang <em>et al</em>., 1997), the Multiple Buddy System and the Paging non-contiguous processor allocation strategies. Our experimental results show that the proposed allocation strategy has solved a number of flaws and drawbacks that have been observed in previously proposed strategies. Further, we observed that our proposed allocation strategy is scalable. We refer to the newly proposed strategy by the “Flexible 2D Buddy System” or F2DBS for short. In our experimental results, we also demonstrated that the F2DBS strategy is more flexible and applies to any 2D mesh of any shape and orientation.

Communication-Load Impact on the Performance of Processor Allocation Strategies in 2-D Mesh Multicomputer Systems

A number of processor allocation strategies have been proposed in literature. A key performance factor that can highlight the difference between these strategies is the amount of communication conducted between the parallel jobs to be allocated. This paper aims to identifying how the density and pattern of communication can affect the performance of these strategies. Compared to the work already presented in literature, we examined a wider range of communication patterns. Other works consider only two types of communication patterns; those are the one-to-all and all-to-all patterns. This paper used the C language to implement the different allocation strategies, and then combined them with the ProcSimity simulation tool. The processor-allocation strategies are examined under the First-Come-First-Serve scheduling strategy. Results show that communication pattern and load are effective factors that have a significant impact on the performance of the processor allocation strategy used.

A New Compacting Non-Contiguous Processor Allocation Algorithm for 2D Mesh Multicomputers

In non-contiguous allocation, a job request can be split into smaller parts that are allocated possibly non-adjacent free sub-meshes rather than always waiting until a single sub-mesh of the requested size and shape is available. Lifting the contiguity condition is expected to reduce processor fragmentation and increase system utilization. However, the distances traversed by messages can be long, and as a result the communication overhead, especially contention, is likely to increase. The extra communication overhead depends on how the allocation request is partitioned and assigned to free sub-meshes. In this paper, a new non-contiguous processor allocation strategy, referred to as Compacting Non-Contiguous Processor Allocation Strategy (CNCPA), is suggested for the 2D mesh multicomputers. In the proposed strategy, a job is compacted into free locations. The selection of the free locations has for goal leaving large free sub-meshes in the system. To evaluate the performance improvement achieved by the proposed strategy and compare it against well-known existing non-contiguous allocation strategies, the authors conducted extensive simulation experiments. The results show that the proposed strategy can improve performance in terms of job turnaround times and system utilization.

Power and performance management for parallel computations in clouds and data centers

We address scheduling independent and precedence constrained parallel tasks on multiple homogeneous processors in a data center with dynamically variable voltage and speed as combinatorial optimization problems. We consider the problem of minimizing schedule length with energy consumption constraint and the problem of minimizing energy consumption with schedule length constraint on multiple processors. Our approach is to use level-by-level scheduling algorithms to deal with precedence constraints. We use a simple system partitioning and processor allocation scheme, which always schedules as many parallel tasks as possible for simultaneous execution. We use two heuristic algorithms for scheduling independent parallel tasks in the same level, i.e., SIMPLE and GREEDY. We adopt a two-level energy/time/power allocation scheme, namely, optimal energy/time allocation among levels of tasks and equal power supply to tasks in the same level. Our approach results in significant performance improvement compared with previous algorithms in scheduling independent and precedence constrained parallel tasks.

Using task migration to improve non-contiguous processor allocation in NoC-based CMPs

In this paper, a processor allocation mechanism for NoC-based chip multiprocessors is presented. Processor allocation is a well-known problem in parallel computer systems and aims to allocate the processing nodes of a multiprocessor to different tasks of an input application at run time. The proposed mechanism targets optimizing the on-chip communication power/latency and relies on two procedures: processor allocation and task migration. Allocation is done by a fast heuristic algorithm to allocate the free processors to the tasks of an incoming application when a new application begins execution. The task-migration algorithm is activated when some application completes execution and frees up the allocated resources. Task migration uses the recently deallocated processors and tries to rearrange the current tasks in order to find a better mapping for them. The proposed method can also capture the dynamic traffic pattern of the network and perform task migration based on the current communication demands of the tasks. Consequently, task migration adapts the task mapping to the current network status. We adopt a non-contiguous processor allocation strategy in which the tasks of the input application are allowed to be mapped onto disjoint regions (groups of processors) of the network. We then use virtual point-to-point circuits, a state-of-the-art fast on-chip connection designed for network-on-chips, to virtually connect the disjoint regions and make the communication latency/power closer to the values offered by contiguous allocation schemes. The experimental results show considerable improvement over existing allocation mechanisms.

Comparative Evaluation of RequestPartitioningbased Processor Allocation Strategies in 2D Meshbased Multicomputers

Partitioning-Based (RPB) allocation schemes remedy the problem of fragmentation by allowing parallel requests to be allocated non-contiguously in case contiguous allocation fails. Two RPB allocation schemes are proposed in literature; the Adaptive Non-Contiguous Allocation (ANCA) and the Bounded-Gradual-Partitioning (BGP) allocation. In ANCA, the frame requested by the parallel job is subdivided into two subframes of equal sizes at the longest dimension of the request. In BGP, requests are gradually partitioned into one large and another small subframe of multicomputers. In this paper, ANCA and BGP based allocation strategies are comparatively evaluated through exhaustive simulation-based experiments. Our experimental results also showed that the ANCA scheme can sustain higher system and communication loads compared to BGP in terms of major system performance metrics. We also observed that, in the BGP approach, increasing the partitioning bound value can slightly improve the performance of the parallel system. Comparatively, increasing the partitioning bound in the ANCA approach could significantly improve the performance of the parallel system.

Energy efficient scheduling of parallel tasks on multiprocessor computers

In this paper, scheduling parallel tasks on multiprocessor computers with dynamically variable voltage and speed are addressed as combinatorial optimization problems. Two problems are defined, namely, minimizing schedule length with energy consumption constraint and minimizing energy consumption with schedule length constraint. The first problem has applications in general multiprocessor and multicore processor computing systems where energy consumption is an important concern and in mobile computers where energy conservation is a main concern. The second problem has applications in real-time multiprocessing systems and environments where timing constraint is a major requirement. Our scheduling problems are defined such that the energy-delay product is optimized by fixing one factor and minimizing the other. It is noticed that power-aware scheduling of parallel tasks has rarely been discussed before. Our investigation in this paper makes some initial attempt to energy-efficient scheduling of parallel tasks on multiprocessor computers with dynamic voltage and speed. Our scheduling problems contain three nontrivial subproblems, namely, system partitioning, task scheduling, and power supplying. Each subproblem should be solved efficiently, so that heuristic algorithms with overall good performance can be developed. The above decomposition of our optimization problems into three subproblems makes design and analysis of heuristic algorithms tractable. A unique feature of our work is to compare the performance of our algorithms with optimal solutions analytically and validate our results experimentally, not to compare the performance of heuristic algorithms among themselves only experimentally. The harmonic system partitioning and processor allocation scheme is used, which divides a multiprocessor computer into clusters of equal sizes and schedules tasks of similar sizes together to increase processor utilization. A three-level energy/time/power allocation scheme is adopted for a given schedule, such that the schedule length is minimized by consuming given amount of energy or the energy consumed is minimized without missing a given deadline. The performance of our heuristic algorithms is analyzed, and accurate performance bounds are derived. Simulation data which validate our analytical results are also presented. It is found that our analytical results provide very accurate estimation of the expected normalized schedule length and the expected normalized energy consumption and that our heuristic algorithms are able to produce solutions very close to optimum.

Hardware implementation of processor allocation schemes for mesh-based chip multiprocessors

Well-designed Processor Allocator (PA) is an important factor in modern Chip MultiProcessors (CMPs). It needs to be fast as well as area and energy efficient, because it is only a small component of the CMP. In this paper, we propose an architecture for such an efficient and fast PA. The PA structure is based on bit map approach and is driven by an Improved First Fit (IFF) algorithm, which is presented and described. Together with the proposed IFF technique, a new Improved Adaptive Scan (IAS) and an Improved Quick Allocation (IQA) algorithms are introduced and discussed and compared with previously known important techniques. The presented synthesis results reveal that the proposed PA achieves good frequency results while, at the same time is characterized by low logic utilization.

An efficient non-contiguous processor allocation strategy for 2D mesh connected multicomputers

In non-contiguous allocation, a job request can be split into smaller parts that are allocated possibly non-adjacent free sub-meshes rather than always waiting until a single sub-mesh of the requested size and shape is available. Lifting the contiguity condition is expected to reduce processor fragmentation and increase system utilization. However, the distances traversed by messages can be long, and as a result the communication overhead, especially contention, is increased. The extra communication overhead depends on how the allocation request is partitioned and assigned to free sub-meshes. In this paper, a new non-contiguous processor allocation strategy, referred to as Greedy-Available-Busy-List, is suggested for the 2D mesh network. Request partitioning in our suggested strategy is based on the sub-meshes available for allocation. To evaluate the performance improvement achieved by our strategy and compare it against well-known existing non-contiguous and contiguous strategies, we conduct extensive simulation runs under the assumption of wormhole routing and three communication patterns, notably one-to-all, all-to-all and random. The results show that the new strategy can reduce the communication overhead and substantially improve performance in terms of job turnaround time and system utilization.

Processor Allocationand Job Scheduling on 3D Mesh Interconnection Networks

Contiguous allocation of parallel jobs usually suffers from the degrading effects of fragmentation, because it requires that the allocated processors be contiguous and have the same topology as the network topology connecting these processors. This paper suggests two non-contiguous processor allocation strategies, referred to as Paging and Greedy-Available respectively, for the 3D mesh network and compares their performance using software simulation against the well-known contiguous First Fit strategy. The comparative evaluation is conducted for two job scheduling strategies, notably first-come-first-served (FCFS) and out-of-order (OO). The results reveal that our proposed non-contiguous strategies exhibit superior performance properties despite the added contention that results from non-contiguity. The results also reveal that the scheduling and allocation strategies both have substantial effect on the performance of contiguous and non-contiguous allocation in that the OO scheduling strategy leads to much better performance than its FCFS counterpart in the 3D mesh.

Distributed dynamic processor allocation for multicomputers

Current processor allocation techniques for highly parallel systems use centralized front-end based algorithms which restrict applied strategies to static allocation, low parallelism, and weak fault tolerance. To lift these restrictions, we are investigating a distributed approach to processor allocation in multicomputers where currently no centralized data structure with information about the state of all processors exists. This approach will allow the implementation of more complex allocation schemes and possibly the consideration of dynamic allocation, where parallel applications would be able to adapt the allocated processor partition to its actual demand at running time, resulting in a more efficient utilization of system resources. Noncontiguous versions of a distributed dynamic processor allocation scheme are proposed and studied in this paper as an alternative for parallel programming models to allow dynamic creation and task deletion. Simulations compare the performance of the proposed dynamic strategies with static counterparts and also with well-known centralized algorithms in an environment with growing and shrinking processor demands. To demonstrate dynamic allocation is feasible with current technologies, results of the experiments are presented for a 96 nodes SCI hpcLine Primergy Server cluster.

A new processor allocation strategy with a high degree of contiguity in mesh-connected multicomputers

Relaxing the contiguity condition in non-contiguous allocation can reduce processor fragmentation and increase processor utilization. However, communication overhead could increase due to the potential increase in message distances. The communication overhead depends on how the allocation request is partitioned and allocated to free sub-meshes. In this paper, a new non-contiguous processor allocation strategy, referred to as Greedy-Available-Busy-List (GABL for short), is suggested for the mesh network, and is compared against the existing non-contiguous and contiguous allocation strategies. To demonstrate the performance gains achieved by our proposed strategy, we have conducted simulation runs under the assumption of wormhole routing technique. The results have revealed that the new strategy can reduce communication overhead and considerably improve performance in terms of the job turnaround time, system utilization, and jobs finish time.

Task migration in all-port wormhole-routed 2D mesh multicomputers

In a mesh multicomputer, submeshes are allocated to perform jobs according to processor allocation schemes, with each task assigned to occupy processors of one submesh with an appropriate size. To assign regions for incoming tasks, task compaction is needed to produce a large contiguous free region. The overhead of task compaction relies mainly on designing an efficient task migration scheme. This paper investigates task migration schemes in 2D wormhole-routed mesh multicomputers with an all-port communication model. Two constraints are given between two submeshes for task migration. Two task migration schemes that follow one of the constraints in 2D mesh multicomputers are then developed. In addition, the proposed schemes are proven to be deadlock-free and congestion-free. Finally, performance analysis is adopted to compare the proposed task migration schemes.

오류가 있는 메쉬 시스템에서의 프로세서 할당 기법

오류가 발생할 수 있는 대규모 멀티컴퓨터 시스템의 프로세싱 자원들을 효율적으로 사용하기 위해서는 신뢰도 높은 프로세서 할당 알고리즘이 요구된다. 본 논문에서는 오류가 있는 메쉬 시스템의 성능을 높일 수 있는 동적이면서 신뢰도 높은 프로세서 할당 기법을 제안한다. 비경계 오류 노드들을 보상할 수 있는 오류프리 상한 또는 하한 경계 노드들을 사용해서 오류가 있는 메쉬 시스템을 최대 볼록 시스템으로 재구성한다. 이 재구성된 비직사각형 메쉬 시스템을 효율적으로 활용하기 위해 기존의 사각형 서브메쉬를 할당 할 수 없을 때 L-모양 서브메쉬를 할당할 수 있다. 시뮬레이션 결과를 통해서 제안하는 기법이 작업응답시간과 시스템 활용도 면에서 다른 기법들보다 우수함을 보인다. Efficient utilization of processing resources in a large multicomputer system with the possibility of fault occurrence depends on the reliable processor management scheme. This paper presents a dynamic and reliable processor allocation strategy to increase the performance of mesh-connected parallel systems with faulty processors The basic idea is to reconfigure a faulty mesh system into a maximum convex system using the fault-free upper or lower boundary nodes to compensate for the non-boundary faulty nodes. To utilize the non-rectangular shaped system parts, our strategy tries to allocate L-shaped submeshes instead of signaling the allocation failure. Extensive simulations show that the strategy performs more efficiently than other strategies in terms of the job response time md the system utilization.

The impact of spatial layout of jobs on I/O hotspots in mesh networks

Network contention hotspots can limit network throughput for parallel disk I/O, even when the interconnection network appears to be sufficiently provisioned. We studied I/O hotspots in mesh networks as a function of the spatial layout of an application's compute nodes relative to the I/O nodes. Our analytical modeling and dynamic simulations show that when I/O nodes are configured on one side of a two-dimensional mesh, realizable I/O throughput is at best bounded by four times the network bandwidth per link. Maximal performance depends on the spatial layout of jobs, and cannot be further improved by adding I/O nodes. Applying these results, we devised a new parallel layout allocation strategy (PLAS) which minimizes I/O hotspots, and approaches the theoretical best case for parallel I/O throughput. Our I/O performance analysis and processor allocation strategy are applicable to a wide range of contemporary and emerging high-performance computing systems.

연속적인 서브메쉬 할당기법에서 단편화를 최소화하는 기법

대규모 멀티컴퓨터 시스템에서 단편화를 줄일 수 있는 적응성 있는 프로세서 할당 기법을 제안한다. 큰 크기의 서브메쉬 할당을 요구하는 작업들의 개수가 적을 경우에도 나머지 작업들의 대기 큐의 지연시간이 증가할 수 있다. 이런 상황에서 할당이 불가능한 기존의 기법들과 달리, L-모양 서브메쉬를 할당할 수 있으며, 할당 가능한 L-모양 서브메쉬를 효율적으로 탐색하는 알고리즘을 개발하였다. 그러므로 FCFS로 스케쥴링되어도, 대기 큐의 지연시간을 줄임으로써 평균응답시간을 줄일 수 있다. 시뮬레이션 결과를 통해서 제안하는 기법이 외부 단편화, 작업응답시간, 그리고 시스템의 활용도 면에서 다른 기법들보다 우수함을 보인다. This paper presents an adaptive processor allocation strategy to reduce fragmentation in a large multi-user multicomputer system. A small number of jobs with unexpectedly large submesh allocation requirements may significantly increase the queuing delay of the rest of jobs. Under such circumstances, our strategy further tries to allocate L-shaped submeshes instead of signaling the allocation failure unlike other strategies. We have developed the efficient algorithm to find the allocatable L-shaped submeshes. Thus, our strategy reduces the mean response time by minimizing the queuing delay, even though jobs are scheduled in an FCFS to preserve fairness. The simulations show that our strategy performs more efficiently than other strategies in terms of the job response time and the system utilization.

A dynamic processor management strategy on the reconfigurable meshes

A reconfigurable mesh consists of a mesh connected topology augmented by a dynamically reconfigurable bus system. The reconfigurable mesh combines two attractive features of massively parallel system, namely constant diameter and the flexibility of the bus system. Efficient utilisation of processing resources in a large, multi user parallel system depends on the reliable processor management scheme. This paper presents a dynamic and reliable processor allocation strategy to increase the performance of mesh connected parallel systems with faulty processors. The basic idea is to reconfigure a faulty mesh system into a maximum convex system using the fault free upper or lower boundary nodes to compensate for the nonboundary faulty nodes. To utilise the nonrectangular shaped system parts, our strategy tries to allocate L shaped submeshes instead of signalling the allocation failure. Extensive simulations show that the strategy performs more efficiently than other strategies in terms of the completion time, the job response time and the system utilisation.

Task migration in n-dimensional wormhole-routed mesh multicomputers

In a mesh multicomputer, performing jobs needs to schedule submeshes according to some processor allocation scheme. In order to assign the incoming jobs to a free submesh, a task compaction scheme is needed to generate a larger contiguous free region. The overhead of compaction depends on the efficiency of the task migration scheme. In this paper, two simple task migration schemes are first proposed in n-dimensional mesh multicomputers with supporting dimension-ordered wormhole routing in one-port communication model. Then, a hybrid scheme which combines advantages of the two schemes is discussed. Finally, we evaluate the performance of all of these proposed approaches.