Power analysis with variable traffic loads for next generation interconnection networks

Power consumption is the most important factor for the consideration of next generation supercomputers. In addition, the requirement of power usages can be even scaled up to more than 300MW (which is nearly equal to the one nuclear power plant) with the conventional networks. On the other hand, hierarchical interconnection networks can be a possible solution to those issues. 3D-TTN is a hierarchical interconnection network where lowest level is configured as the 3Dtorus network, following the 2Dtorus network at the higher-level networks. The main focus for this paper is the power analysis with variable traffic load along with the fault tolerance, cost, packing density and message traffic density of 3D-TTN comparing against various other networks. In our early research, 3D-TTN has achieved near about 21% better diameter performance, 12% better average distance performance and eventually required about 32.48% less router power usage at the lowest level than the 5Dtorus network for 1% traffic load. This paper shows the power comparison with the router and link power rather than considering the router power only. Our analysis shows that 3DTTN will require about 39.96% less router and link power than the 5Dtorus network for 10% traffic. With 30% traffic load, 3DTTN will require about 38.42% less power than the 5Dtorus network for the on-chip network. Even considering some topological parameters, 3D-TTN could also achieve some desirable performance by comparing other networks

Efficient Multicast Algorithms for Mesh and Torus Networks

With the increasing popularity of multicomputers, efficient way of communication within its processors has become a popular area of research. Multicomputers refer to a computer system that has multiple processors, they have high computational power and they can perform multiple tasks concurrently. Mesh and Torus are some of the commonly used network topologies in building multicomputer systems. Their performance highly depends on the underlying network communication such as multicast. Multicast is a communication method in which a message is sent from a source node to a certain number of destinations. Two major parameters used to evaluate multicast are time that a multicast process takes to deliver the message to all destinations and traffic that indicates the number of links used for this process. Research indicates that in general, it is NP- complete to find an optimal multicasting algorithm which is efficient on both time and traffic. This thesis suggests two new algorithms to achieve multicast in mesh and torus networks. Extensive simulations of these algorithms show that in practice they perform better than existing ones

Exploring Adaptive Implementation of On-Chip Networks

As technology geometries have shrunk to the deep submicron regime, the communication delay and power consumption of global interconnections in high performance Multi- Processor Systems-on-Chip (MPSoCs) are becoming a major bottleneck. The Network-on- Chip (NoC) architecture paradigm, based on a modular packet-switched mechanism, can address many of the on-chip communication issues such as performance limitations of long interconnects and integration of large number of Processing Elements (PEs) on a chip. The choice of routing protocol and NoC structure can have a significant impact on performance and power consumption in on-chip networks. In addition, building a high performance, area and energy efficient on-chip network for multicore architectures requires a novel on-chip router allowing a larger network to be integrated on a single die with reduced power consumption. On top of that, network interfaces are employed to decouple computation resources from communication resources, to provide the synchronization between them, and to achieve backward compatibility with existing IP cores. Three adaptive routing algorithms are presented as a part of this thesis. The first presented routing protocol is a congestion-aware adaptive routing algorithm for 2D mesh NoCs which does not support multicast (one-to-many) traffic while the other two protocols are adaptive routing models supporting both unicast (one-to-one) and multicast traffic. A streamlined on-chip router architecture is also presented for avoiding congested areas in 2D mesh NoCs via employing efficient input and output selection. The output selection utilizes an adaptive routing algorithm based on the congestion condition of neighboring routers while the input selection allows packets to be serviced from each input port according to its congestion level. Moreover, in order to increase memory parallelism and bring compatibility with existing IP cores in network-based multiprocessor architectures, adaptive network interface architectures are presented to use multiple SDRAMs which can be accessed simultaneously. In addition, a smart memory controller is integrated in the adaptive network interface to improve the memory utilization and reduce both memory and network latencies. Three Dimensional Integrated Circuits (3D ICs) have been emerging as a viable candidate to achieve better performance and package density as compared to traditional 2D ICs. In addition, combining the benefits of 3D IC and NoC schemes provides a significant performance gain for 3D architectures. In recent years, inter-layer communication across multiple stacked layers (vertical channel) has attracted a lot of interest. In this thesis, a novel adaptive pipeline bus structure is proposed for inter-layer communication to improve the performance by reducing the delay and complexity of traditional bus arbitration. In addition, two mesh-based topologies for 3D architectures are also introduced to mitigate the inter-layer footprint and power dissipation on each layer with a small performance penalty.Siirretty Doriast

Efficient processor allocation strategies for mesh-connected multicomputers

Abstract Efficient processor allocation and job scheduling algorithms are critical if the full computational power of large-scale multicomputers is to be harnessed effectively. Processor allocation is responsible for selecting the set of processors on which parallel jobs are executed, whereas job scheduling is responsible for determining the order in which the jobs are executed. Many processor allocation strategies have been devised for mesh-connected multicomputers and these can be divided into two main categories: contiguous and non-contiguous. In contiguous allocation, jobs are allocated distinct contiguous processor sub-meshes for the duration of their execution. Such a strategy could lead to high processor fragmentation which degrades system performance in terms of, for example, the turnaround time and system utilisation. In non-contiguous allocation, a job can execute on multiple disjoint smaller sub-meshes rather than waiting until a single sub-mesh of the requested size and shape is available. Although non-contiguous allocation increases message contention inside the network, lifting the contiguity condition can reduce processor fragmentation and increase system utilisation. Processor fragmentation can be of two types: internal and external. The former occurs when more processors are allocated to a job than it requires while the latter occurs when there are free processors enough in number to satisfy another job request, but they are not allocated to it because they are not contiguous. A lot of efforts have been devoted to reducing fragmentation, and a number of contiguous allocation strategies have been devised to recognize complete sub-meshes during allocation. Most of these strategies have been suggested for 2D mesh-connected multicomputers. However, although the 3D mesh has been the underlying network topology for a number of important multicomputers, there has been relatively little activity with regard to designing similar strategies for such a network. The very few contiguous allocation strategies suggested for the 3D mesh achieve complete sub-mesh recognition ability only at the expense of a high allocation overhead (i.e., allocation and de-allocation time). Furthermore, the allocation overhead in the existing contiguous strategies often grows with system size. The main challenge is therefore to devise an efficient contiguous allocation strategy that can exhibit good performance (e.g., a low job turnaround time and high system utilisation) with a low allocation overhead. The first part of the research presents a new contiguous allocation strategy, referred to as Turning Busy List (TBL), for 3D mesh-connected multicomputers. The TBL strategy considers only those available free sub-meshes which border from the left of those already allocated sub-meshes or which have their left boundaries aligned with that of the whole mesh network. Moreover TBL uses an efficient scheme to facilitate the detection of such available sub-meshes while maintaining a low allocation overhead. This is achieved through maintaining a list of allocated sub-meshes in order to efficiently determine the processors that can form an allocation sub-mesh for a new allocation request. The new strategy is able to identify a free sub-mesh of the requested size as long as it exists in the mesh. Results from extensive simulations under various operating loads reveal that TBL manages to deliver competitive performance (i.e., low turnaround times and high system utilisation) with a much lower allocation overhead compared to other well-known existing strategies. Most existing non-contiguous allocation strategies that have been suggested for the mesh suffer from several problems that include internal fragmentation, external fragmentation, and message contention inside the network. Furthermore, the allocation of processors to job requests is not based on free contiguous sub-meshes in these existing strategies. The second part of this research proposes a new non-contiguous allocation strategy, referred to as Greedy Available Busy List (GABL) strategy that eliminates both internal and external fragmentation and alleviates the contention in the network. GABL combines the desirable features of both contiguous and non-contiguous allocation strategies as it adopts the contiguous allocation used in our TBL strategy. Moreover, GABL is flexible enough in that it could be applied to either the 2D or 3D mesh. However, for the sake of the present study, the new non-contiguous allocation strategy is discussed for the 2D mesh and compares its performance against that of well-known non-contiguous allocation strategies suggested for this network. One of the desirable features of GABL is that it can maintain a high degree of contiguity between processors compared to the previous allocation strategies. This, in turn, decreases the number of sub-meshes allocated to a job, and thus decreases message distances, resulting in a low inter-processor communication overhead. The performance analysis here indicates that the new proposed strategy has lower turnaround time than the previous non-contiguous allocation strategies for most considered cases. Moreover, in the presence of high message contention due to heavy network traffic, GABL exhibits superior performance in terms of the turnaround time over the previous contiguous and non-contiguous allocation strategies. Furthermore, GABL exhibits a high system utilisation as it manages to eliminate both internal and external fragmentation. The performance of many allocation strategies including the ones suggested above, has been evaluated under the assumption that job execution times follow an exponential distribution. However, many measurement studies have convincingly demonstrated that the execution times of certain computational applications are best characterized by heavy-tailed job execution times; that is, many jobs have short execution times and comparatively few have very long execution times. Motivated by this observation, the final part of this thesis reviews the performance of several contiguous allocation strategies, including TBL, in the context of heavy-tailed distributions. This research is the first to analyze the performance impact of heavy-tailed job execution times on the allocation strategies suggested for mesh-connected multicomputers. The results show that the performance of the contiguous allocation strategies degrades sharply when the distribution of job execution times is heavy-tailed. Further, adopting an appropriate scheduling strategy, such as Shortest-Service-Demand (SSD) as opposed to First-Come-First-Served (FCFS), can significantly reduce the detrimental effects of heavy-tailed distributions. Finally, while the new contiguous allocation strategy (TBL) is as good as the best competitor of the previous contiguous allocation strategies in terms of job turnaround time and system utilisation, it is substantially more efficient in terms of allocation overhead

On Near Optimal Time and Dynamic Delay and Delay Variation Multicast Algorithms

Multicast is one of the most prevalent communication modes in computer networks. A plethora of systems and applications today rely on multicast communication to disseminate traffic including but not limited to teleconferencing, videoconferencing, stock exchanges, supercomputers, software update distribution, distributed database systems, and gaming. This dissertation elaborates and addresses key research challenges and problems related to the design and implementation of multicast algorithms. In particular, it investigates the problems of (1) Designing near optimal multicast time algorithms for mesh and torus connected systems and (2) Designing efficient algorithms for Delay and Delay Variation Bounded Multicast (DVBM). To achieve the first goal, improvements on four tree based multicast algorithms are made: Modified PAIR (MPAIR), Modified DIAG (MDIAG), Modified MIN (MMIN), and Modified DIST (MDIST). The proof that MDIAG generates optimal or optimal plus one multicast time in 2-Dimensional (2D) mesh networks is provided. The hybrid version of MDIAG (HMDIAG) is designed, that gives a 3-additive approximation algorithm on multicast time in 2D torus networks. To make HMDIAG applicable on systems using higher dimensional meshes and tori, it is extended and the proof that it gives a (2n-1)-additive approximation algorithm on multicast time in nD torus networks is given. To address the second goal, Directional Core Selection (DCS) algorithm for core selection and DVBM Tree generation is designed. To further reduce the delay variation of trees generated by DCS, a k-shortest-path based algorithm, Build Lower Variation Tree (BLVT) is designed. To tackle dynamic join/leave requests to the ongoing multicast session, the dynamic version of both algorithms is given that responds to requests by reorganizing the tree and avoiding session disruption. To solve cases where single-core based algorithms fail to construct a DVBM tree, a dynamic three-phase algorithm, Multi-core DVBM Trees (MCDVBMT) is designed, that semi-matches group members to core nodes

Routing and Wavelength Assignment for Multicast Communication in Optical Network-on-Chip

An Optical Network-on-Chip (ONoC) is an emerging chip-level optical interconnection technology to realise high-performance and power-efficient inter-core communication for many-core processors. Within the field, multicast communication is one of the most important inter-core communication forms. It is not only widely used in parallel computing applications in Chip Multi-Processors (CMPs), but also common in emerging areas such as neuromorphic computing. While many studies have been conducted on designing ONoC architectures and routing schemes to support multicast communication, most existing solutions adopt the methods that were initially proposed for electrical interconnects. These solutions can neither fully take advantage of optical communication nor address the special requirements of an ONoC. Moreover, most of them focus only on the optimisation of one multicast, which limits the practical applications because real systems often have to handle multiple multicasts requested from various applications. Hence, this thesis will address the design of a high-performance communication scheme for multiple multicasts by taking into account the unique characteristics and constraints of an ONoC. This thesis studies the problem from a network-level perspective. The design methodology is to optimally route all multicasts requested simultaneously from the applications in an ONoC, with the objective of efficiently utilising available wavelengths. The novelty is to adopt multicast-splitting strategies, where a multicast can be split into several sub-multicasts according to the distribution of multicast nodes, in order to reduce the conflicts of different multicasts. As routing and wavelength assignment problem is an NP-hard problem, heuristic approaches that use the multicast-splitting strategy are proposed in this thesis. Specifically, three routing and wavelength assignment schemes for multiple multicasts in an ONoC are proposed for different problem domains. Firstly, PRWAMM, a Path-based Routing and Wavelength Assignment for Multiple Multicasts in an ONoC, is proposed. Due to the low manufacture complexity requirement of an ONoC, e.g., no splitters, path-based routing is studied in PRWAMM. Two wavelength-assignment strategies for multiple multicasts under path-based routing are proposed. One is an intramulticast wavelength assignment, which assigns wavelength(s) for one multicast. The other is an inter-multicast wavelength assignment, which assigns wavelength(s) for different multicasts, according to the distributions of multicasts. Simulation results show that PRWAMM can reduce the average number of wavelengths by 15% compared to other path-based schemes. Secondly, RWADMM, a Routing and Wavelength Assignment scheme for Distribution-based Multiple Multicasts in a 2D ONoC, is proposed. Because path-based routing lacks flexibility, it cannot reduce the link conflicts effectively. Hence, RWADMM is designed, based on the distribution of different multicasts, which includes two algorithms. One is an optimal routing and wavelength assignment algorithm for special distributions of multicast nodes. The other is a heuristic routing and wavelength assignment algorithm for random distributions of multicast nodes. Simulation results show that RWADMM can reduce the number of wavelengths by 21.85% on average, compared to the state-of-the-art solutions in a 2D ONoC. Thirdly, CRRWAMM, a Cluster-based Routing and Reusable Wavelength Assignment scheme for Multiple Multicasts in a 3D ONoC, is proposed. Because of the different architectures with a 2D ONoC (e.g., the layout of nodes, optical routers), the methods designed for a 2D ONoC cannot be simply extended to a 3D ONoC. In CRRWAMM, the distribution of multicast nodes in a mesh-based 3D ONoC is analysed first. Then, routing theorems for special instances are derived. Based on the theorems, a general routing scheme, which includes a cluster-based routing method and a reusable wavelength assignment method, is proposed. Simulation results show that CRRWAMM can reduce the number of wavelengths by 33.2% on average, compared to other schemes in a 3D ONoC. Overall, the three routing and wavelength assignment schemes can achieve high-performance multicast communication for multiple multicasts of their problem domains in an ONoC. They all have the advantages of a low routing complexity, a low wavelength requirement, and good scalability, compared to their counterparts, respectively. These methods make an ONoC a flexible high-performance computing platform to execute various parallel applications with different multicast requirements. As future work, I will investigate the power consumption of various routing schemes for multicasts. Using a multicast-splitting strategy may increase power consumption since it needs different wavelengths to send packets to different destinations for one multicast, though the reduction of wavelengths used in the schemes can also potentially decrease overall power consumption. Therefore, how to achieve the best trade-off between the total number of wavelengths used and the number of sub-multicasts in order to reduce power consumption will be interesting future research