This paper presents the design and implementation of a hip range of motion (ROM) estimation method that is capable of fine-grained estimation during total hip replacement (THR) surgery. Our method is based on two acceleration strategies: (1) adaptive mesh refinement (AMR) for complexity reduction and (2) parallelization for further acceleration. On the assumption that the hip ROM is a single closed region, the AMR strategy reduces the complexity for N N N stance configurations from O(N3) to O(ND), where 2≤D≤3 and D is a data-dependent value that can be approximated by 2 in most cases. The parallelization strategy employs the master-worker paradigm with multiple task queues, reducing synchronization between processors with load balancing. The experimental results indicate that the implementation on a cluster of 64 PCs completes estimation of 360360180 stance configurations in 20 seconds, playing a key role in selecting and aligning the optimal combination of artificial joint components during THR surgery.

High performance scientific and engineering applications running on clusters have different communication requirements. Current cluster configurations typically provide multiple network interfaces per node and multiple interconnections among nodes. However, transport protocols such as TCP do not utilize existing multiple network interfaces to enhance communication performance. This paper introduces a new configurable communication model utilizing multiple interconnections. The model adds mechanisms to manage and enhance the overall communication performance of clusters. These configurations include the use of parallel message transfers, the separation of the transfer channels between small messages and large messages, and load balancing among the channels. The main advantages of the model are: (1) providing a flexible, enhanced network infrastructure, (2) hiding the technical details of the heterogeneous network resources from the applications, and (3) providing an easy and flexible way to extend the network capacities for specific nodes. To illustrate the advantages and performance enhancements of the model, a prototype was implemented to experimentally evaluate the cluster network performance, which showed considerable gains.

Cluster computation has been used in the applications that demand performance, reliability, and availability, such as cluster server groups, large-scale scientific computations, distributed databases, distributed media-on-demand servers and search engines etc. In those applications, multicast can play the vital roles for the information dissemination among groups of servers and users. This paper proposes a set of novel efficient fault-tolerant multicast routing algorithms on hypercube interconnection of cluster computers using multicast shared tree approach. We present some new algorithms for selecting an optimal core (root) and constructing the shared tree so as to minimize the average delay for multicast messages. Simulation results indicate that our algorithms are efficient in the senses of short end-to-end average delay, load balance and less resource utilizations over hypercube cluster interconnection networks.

RHiNET-3/SW is the third-generation switch used in the RHiNET-3 system. It provides both low-latency processing and flexible connection due to its use of a credit-based flow-control mechanism, topology-free routing, and deadlock-free routing. The aggregate throughput of RHiNET-3/SW is 80 Gbps, and the latency is 140 ns. RHiNET-3/SW also provides a hop-by-hop retransmission mechanism. Simulation demonstrated that the effective throughput at a node in a 64-node torus RHiNET-3 system is equivalent to the effective throughput of a 64-bit 33-MHz PCI bus and that the performance of RHiNET-3/SW almost equals or exceeds the best performance of RHiNET-2/SW, the second-generation switch. Although credit-based flow control requires 26% more gates than rate-based flow control to manage the virtual channels (VCs), it requires less VC memory than rate-based flow control. Moreover, its use in a network system reduces latency and increases the maximum throughput compared to rate-based flow control.

We conducted research and development of Distributed Supercomputing Environment (DSE) based on distributed shared memory model to serve as a cluster computing environment to provide parallel processing facilities. Shared memory model and message passing model are well-known typical models of parallel processing. It is desired that hybrid programming environment will make the best use of the prominent features of both models. Consequently, we add a new message passing mechanism to present DSE, and create a prototype called Hybrid DSE as a hybrid model based cluster computing environment. In this paper, we describe the implementation of a message passing mechanism on DSE and performance evaluation of Hybrid DSE.