Non-contiguous Processor Allocation Strategies Research Articles

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.

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.

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.

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.

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.