On the performance of broadcast algorithms in interconnection networks

Broadcast Communication is among the most primitive collective capabilities of any message passing network. Broadcast algorithms for the mesh have been widely reported in the literature. However, most existing algorithms have been studied within limited conditions, such as light traffic load and fixed network sizes. In other words, most of these algorithms have not been studied at different Quality of Service (QoS) levels. In contrast, this study examines the broadcast operation, taking into account the scalability, parallelism, a wide range of traffic loads through the propagation of broadcast messages. To the best of our knowledge, this study is the first to consider the issue of broadcast latency at both the network and node levels across different traffic loads. Results are shown from a comparative analysis confirming that the coded-path based broadcast algorithms exhibit superior performance characteristics over some existing algorithms

Isomorphic Strategy for Processor Allocation in k-Ary n-Cube Systems

Due to its topological generality and flexibility, the k-ary n-cube architecture has been actively researched for various applications. However, the processor allocation problem has not been adequately addressed for the k-ary n-cube architecture, even though it has been studied extensively for hypercubes and meshes. The earlier k-ary n-cube allocation schemes based on conventional slice partitioning suffer from internal fragmentation of processors. In contrast, algorithms based on job-based partitioning alleviate the fragmentation problem but require higher time complexity. This paper proposes a new allocation scheme based on isomorphic partitioning, where the processor space is partitioned into higher dimensional isomorphic subcubes. The proposed scheme minimizes the fragmentation problem and is general in the sense that any size request can be supported and the host architecture need not be isomorphic. Extensive simulation study reveals that the proposed scheme significantly outperforms earlier schemes in terms of mean response time for practical size k-ary and n-cube architectures. The simulation results also show that reduction of external fragmentation is more substantial than internal fragmentation with the proposed scheme

Isomorphic Strategy for Processor Allocation in k-Ary n-Cube Systems

Due to its topological generality and flexibility, the k-ary n-cube architecture has been actively researched for various applications. However, the processor allocation problem has not been adequately addressed for the k-ary n-cube architecture, even though it has been studied extensively for hypercubes and meshes. The earlier k-ary n-cube allocation schemes based on conventional slice partitioning suffer from internal fragmentation of processors. In contrast, algorithms based on job-based partitioning alleviate the fragmentation problem but require higher time complexity. This paper proposes a new allocation scheme based on isomorphic partitioning, where the processor space is partitioned into higher dimensional isomorphic subcubes. The proposed scheme minimizes the fragmentation problem and is general in the sense that any size request can be supported and the host architecture need not be isomorphic. Extensive simulation study reveals that the proposed scheme significantly outperforms earlier schemes in terms of mean response time for practical size k-ary and n-cube architectures. The simulation results also show that reduction of external fragmentation is more substantial than internal fragmentation with the proposed scheme

New Fault Tolerant Multicast Routing Techniques to Enhance Distributed-Memory Systems Performance

Distributed-memory systems are a key to achieve high performance computing and the most favorable architectures used in advanced research problems. Mesh connected multicomputer are one of the most popular architectures that have been implemented in many distributed-memory systems. These systems must support communication operations efficiently to achieve good performance. The wormhole switching technique has been widely used in design of distributed-memory systems in which the packet is divided into small flits. Also, the multicast communication has been widely used in distributed-memory systems which is one source node sends the same message to several destination nodes. Fault tolerance refers to the ability of the system to operate correctly in the presence of faults. Development of fault tolerant multicast routing algorithms in 2D mesh networks is an important issue. This dissertation presents, new fault tolerant multicast routing algorithms for distributed-memory systems performance using wormhole routed 2D mesh. These algorithms are described for fault tolerant routing in 2D mesh networks, but it can also be extended to other topologies. These algorithms are a combination of a unicast-based multicast algorithm and tree-based multicast algorithms. These algorithms works effectively for the most commonly encountered faults in mesh networks, f-rings, f-chains and concave fault regions. It is shown that the proposed routing algorithms are effective even in the presence of a large number of fault regions and large size of fault region. These algorithms are proved to be deadlock-free. Also, the problem of fault regions overlap is solved. Four essential performance metrics in mesh networks will be considered and calculated; also these algorithms are a limited-global-information-based multicasting which is a compromise of local-information-based approach and global-information-based approach. Data mining is used to validate the results and to enlarge the sample. The proposed new multicast routing techniques are used to enhance the performance of distributed-memory systems. Simulation results are presented to demonstrate the efficiency of the proposed algorithms

Performance evaluation of distributed crossbar switch hypermesh

The interconnection network is one of the most crucial components in any multicomputer as it greatly influences the overall system performance. Several recent studies have suggested that hypergraph networks, such as the Distributed Crossbar Switch Hypermesh (DCSH), exhibit superior topological and performance characteristics over many traditional graph networks, e.g. k-ary n-cubes. Previous work on the DCSH has focused on issues related to implementation and performance comparisons with existing networks. These comparisons have so far been confined to deterministic routing and unicast (one-to-one) communication. Using analytical models validated through simulation experiments, this thesis extends that analysis to include adaptive routing and broadcast communication. The study concentrates on wormhole switching, which has been widely adopted in practical multicomputers, thanks to its low buffering requirement and the reduced dependence of latency on distance under low traffic. Adaptive routing has recently been proposed as a means of improving network performance, but while the comparative evaluation of adaptive and deterministic routing has been widely reported in the literature, the focus has been on graph networks. The first part of this thesis deals with adaptive routing, developing an analytical model to measure latency in the DCSH, and which is used throughout the rest of the work for performance comparisons. Also, an investigation of different routing algorithms in this network is presented. Conventional k-ary n-cubes have been the underlying topology of contemporary multicomputers, but it is only recently that adaptive routing has been incorporated into such systems. The thesis studies the relative performance merits of the DCSH and k-ary n-cubes under adaptive routing strategy. The analysis takes into consideration real-world factors, such as router complexity and bandwidth constraints imposed by implementation technology. However, in any network, the routing of unicast messages is not the only factor in traffic control. In many situations (for example, parallel iterative algorithms, memory update and invalidation procedures in shared memory systems, global notification of network errors), there is a significant requirement for broadcast traffic. The DCSH, by virtue of its use of hypergraph links, can implement broadcast operations particularly efficiently. The second part of the thesis examines how the DCSH and k-ary n-cube performance is affected by the presence of a broadcast traffic component. In general, these studies demonstrate that because of their relatively high diameter, k-ary n-cubes perform poorly when message lengths are short. This is consistent with earlier more simplistic analyses which led to the proposal for the express-cube, an enhancement of the basic k-ary n-cube structure, which provides additional express channels, allowing messages to bypass groups of nodes along their paths. The final part of the thesis investigates whether this "partial bypassing" can compete with the "total bypassing" capability provided inherently by the DCSH topology

Performance analysis of wormhole routing in multicomputer interconnection networks

Perhaps the most critical component in determining the ultimate performance potential of a multicomputer is its interconnection network, the hardware fabric supporting communication among individual processors. The message latency and throughput of such a network are affected by many factors of which topology, switching method, routing algorithm and traffic load are the most significant. In this context, the present study focuses on a performance analysis of k-ary n-cube networks employing wormhole switching, virtual channels and adaptive routing, a scenario of especial interest to current research. This project aims to build upon earlier work in two main ways: constructing new analytical models for k-ary n-cubes, and comparing the performance merits of cubes of different dimensionality. To this end, some important topological properties of k-ary n-cubes are explored initially; in particular, expressions are derived to calculate the number of nodes at/within a given distance from a chosen centre. These results are important in their own right but their primary significance here is to assist in the construction of new and more realistic analytical models of wormhole-routed k-ary n-cubes. An accurate analytical model for wormhole-routed k-ary n-cubes with adaptive routing and uniform traffic is then developed, incorporating the use of virtual channels and the effect of locality in the traffic pattern. New models are constructed for wormhole k-ary n-cubes, with the ability to simulate behaviour under adaptive routing and non-uniform communication workloads, such as hotspot traffic, matrix-transpose and digit-reversal permutation patterns. The models are equally applicable to unidirectional and bidirectional k-ary n-cubes and are significantly more realistic than any in use up to now. With this level of accuracy, the effect of each important network parameter on the overall network performance can be investigated in a more comprehensive manner than before. Finally, k-ary n-cubes of different dimensionality are compared using the new models. The comparison takes account of various traffic patterns and implementation costs, using both pin-out and bisection bandwidth as metrics. Networks with both normal and pipelined channels are considered. While previous similar studies have only taken account of network channel costs, our model incorporates router costs as well thus generating more realistic results. In fact the results of this work differ markedly from those yielded by earlier studies which assumed deterministic routing and uniform traffic, illustrating the importance of using accurate models to conduct such analyses

Architectural Support for Efficient Communication in Future Microprocessors

Traditionally, the microprocessor design has focused on the computational aspects of the problem at hand. However, as the number of components on a single chip continues to increase, the design of communication architecture has become a crucial and dominating factor in defining performance models of the overall system. On-chip networks, also known as Networks-on-Chip (NoC), emerged recently as a promising architecture to coordinate chip-wide communication. Although there are numerous interconnection network studies in an inter-chip environment, an intra-chip network design poses a number of substantial challenges to this well-established interconnection network field. This research investigates designs and applications of on-chip interconnection network in next-generation microprocessors for optimizing performance, power consumption, and area cost. First, we present domain-specific NoC designs targeted to large-scale and wire-delay dominated L2 cache systems. The domain-specifically designed interconnect shows 38% performance improvement and uses only 12% of the mesh-based interconnect. Then, we present a methodology of communication characterization in parallel programs and application of characterization results to long-channel reconfiguration. Reconfigured long channels suited to communication patterns enhance the latency of the mesh network by 16% and 14% in 16-core and 64-core systems, respectively. Finally, we discuss an adaptive data compression technique that builds a network-wide frequent value pattern map and reduces the packet size. In two examined multi-core systems, cache traffic has 69% compressibility and shows high value sharing among flows. Compression-enabled NoC improves the latency by up to 63% and saves energy consumption by up to 12%

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

Static and Dynamic Scheduling for Effective Use of Multicore Systems

Multicore systems have increasingly gained importance in high performance computers. Compared to the traditional microarchitectures, multicore architectures have a simpler design, higher performance-to-area ratio, and improved power efficiency. Although the multicore architecture has various advantages, traditional parallel programming techniques do not apply to the new architecture efficiently. This dissertation addresses how to determine optimized thread schedules to improve data reuse on shared-memory multicore systems and how to seek a scalable solution to designing parallel software on both shared-memory and distributed-memory multicore systems. We propose an analytical cache model to predict the number of cache misses on the time-sharing L2 cache on a multicore processor. The model provides an insight into the impact of cache sharing and cache contention between threads. Inspired by the model, we build the framework of affinity based thread scheduling to determine optimized thread schedules to improve data reuse on all the levels in a complex memory hierarchy. The affinity based thread scheduling framework includes a model to estimate the cost of a thread schedule, which consists of three submodels: an affinity graph submodel, a memory hierarchy submodel, and a cost submodel. Based on the model, we design a hierarchical graph partitioning algorithm to determine near-optimal solutions. We have also extended the algorithm to support threads with data dependences. The algorithms are implemented and incorporated into a feedback directed optimization prototype system. The prototype system builds upon a binary instrumentation tool and can improve program performance greatly on shared-memory multicore architectures. We also study the dynamic data-availability driven scheduling approach to designing new parallel software on distributed-memory multicore architectures. We have implemented a decentralized dynamic runtime system. The design of the runtime system is focused on the scalability metric. At any time only a small portion of a task graph exists in memory. We propose an algorithm to solve data dependences without process cooperation in a distributed manner. Our experimental results demonstrate the scalability and practicality of the approach for both shared-memory and distributed-memory multicore systems. Finally, we present a scalable nonblocking topology-aware multicast scheme for distributed DAG scheduling applications