We have developed a novel basic technology for terahertz (THz) imaging, which allows detection and identification of chemicals by introducing the component spatial pattern analysis. The spatial distributions of the chemicals were obtained from terahertz multispectral transillumination images, using absorption spectra previously measured with a widely tunable THz-wave parametric oscillator. We have also separated the component spatial patterns of frequency-dependent absorptions in chemicals and frequency-independent components such as plastic, paper and measurement noise in THz spectroscopic images. Further we have applied this technique to the detection and identification of illicit drugs concealed in envelopes.

In this paper we apply a parallel adaptive solution algorithm to simulate nanoscale double-gate metal-oxide-semiconductor field effect transistors (MOSFETs) on a personal computer (PC)-based Linux cluster with the message passing interface (MPI) libraries. Based on a posteriori error estimation, the triangular mesh generation, the adaptive finite volume method, the monotone iterative method, and the parallel domain decomposition algorithm, a set of two-dimensional quantum correction hydrodynamic (HD) equations is solved numerically on our constructed cluster system. This parallel adaptive simulation methodology with 1-irregular mesh was successfully developed and applied to deep-submicron semiconductor device simulation in our recent work. A 10 nm n-type double-gate MOSFET is simulated with the developed parallel adaptive simulator. In terms of physical quantities and refined adaptive mesh, simulation results demonstrate very good accuracy and computational efficiency. Benchmark results, such as load-balancing, speedup, and parallel efficiency are achieved and exhibit excellent parallel performance. On a 16 nodes PC-based Linux cluster, the maximum difference among CPUs is less than 6%. A 12.8 times speedup and 80% parallel efficiency are simultaneously attained with respect to different simulation cases.

This letter proposes a low-power tournament branch predictor, in which the number of accesses to the branch predictors (local predictor or global predictor) is reduced. Analysis results with Samsung Memory Compiler show that the proposed branch predictor reduces the power consumption by 24-45%, compared to the conventional tournament branch predictor, not requiring any additional storage arrays, not incurring any additional delay and never harming accuracy.

Traditional Web cache servers based on HTTP and ICP infrastructure tend to have higher hardware and management cost, have difficulty in availability, automatic and dynamic reconfiguration, and may have slow links to some users. We find that peer-to-peer technology can help solve these problems. The peer cache service (PCS) we proposed here leverages each peer's local cache, similar access patterns, fully distributed coordination, and fast communication channels to enhance response time, scale of cacheable objects, and availability. Moreover, incorporating goals and strategies such as making the protocol lightweight and mutually compatible with existing cache infrastructure, supporting mobile devices, undertaking dynamic three-level caching, and exchanging cache meta-information further improve the effectiveness and differentiate our work from other similar-at-first-glance P2P Web cache systems.

Fault-tolerance is an essential feature of the distributed systems where the possibility of a failure increases with the growth of the system. In spite of extensive researches over two decades, fault-tolerance systems have not succeeded in practical use. It is due to the high overhead and the unhandiness of the previous fault-tolerance systems. In this paper, we propose MPICH-GF, a user-transparent checkpointing system for grid-enabled MPICH. Our objectives are to fill the gap between the theory and the practice of fault-tolerance systems, and to provide a checkpointing-recovery system for grids. To build a fault-tolerant MPICH version, we have designed task migration, dynamic process management, and atomic message transfer. MPICH-GF requires no modification of application source codes, and it affects the MPICH communication characteristics as less as possible. The features of MPICH-GF are that it supports the direct message transfer mode and that all of the implementation has been done at the lower layer, that is, the abstract device level. We have evaluated MPICH-GF using NPB applications on Globus middleware.

Techniques for automatic program recognition, at the algorithmic level, could be of high interest for the area of Software Maintenance, in particular for knowledge based reengineering, because the selection of suitable restructuring strategies is mainly driven by algorithmic features of the code. In this paper an automated hierarchical concept parsing recognition technique, and a formalism for the specification of algorithmic concepts, is presented. Based on this technique, the design and development of ALCOR, a production rule based system for automatic recognition of algorithmic concepts within programs, aimed at support of knowledge based reengineering for high performance, is presented.

In a Distributed Computing Systems (DCS) tasks submitted to it, are usually partitioned into different modules and these modules may be allocated to different processing nodes so as to achieve minimum turn around time of the tasks utilizing the maximum resources of the existing system such as CPU speed, memory capacities etc. The problem lies on how to obtain the optimal allocation of these multiple tasks by keeping in mind that no processing node is overloaded due to this allocation. This paper proposes an algorithm A*RS, using well-known A*, which aims to reduce the search space and time for task allocation. It aims at minimization of turn around time of tasks in the way so that processing nodes do not become overloaded due to this allocation. Our experimental results justify the claims with necessary supports by comparing it with the earlier algorithm for multiple tasks allocation.

The availability of a low cost hardware has increased the development of distributed systems, by making then more and more accessible. In order to optimize the resources allocation on the distributed systems, some load balancing algorithms have been proposed. These algorithms distribute the application loads over the environment computers, make homogeneous the occupation of the whole environment and increase the application performance. This equal distribution prevents certain computers to get overloaded, to the detriment of the idleness of the other ones. This article proposes and analyzes the TLBAGrid, a load balancing algorithm for Grid computing environments.

For network computing on desktop machines, fast execution of Java bytecode programs is essential because these machines are expected to run substantial application programs written in Java. We believe higher Java performance can be achieved by exploiting instruction-level parallelism (ILP) in the context of Java JIT compilation. This paper introduces VLaTTe, a Java JIT compiler for VLIW machines that performs efficient scheduling while doing fast register allocation. It is an extended version of our previous JIT compiler for RISC machines called LaTTe whose translation overhead is low (i.e., consistently taking one or two seconds for SPECJVM98 benchmarks) due to its fast register allocation. VLaTTe adds the scheduling capability onto the same framework of register allocation, with a constraint for precise in-order exception handling which guarantees the same Java exception behavior with the original bytecode program. Our experimental results on the SPECJVM98 benchmarks show that VLaTTe achieves a geometric mean of useful IPC 1.7 (2-ALU), 2.1 (4-ALU), and 2.3 (8-ALU), while the scheduling/allocation overhead is 3.6 times longer than LaTTe's on average, which appears to be reasonable.

DualFS is a next-generation journaling file system which has the same consistency guaranties as traditional journaling file systems but better performance. This paper introduces three new enhancements which significantly improve DualFS performance during normal operation, and presents different experimental results which compare DualFS and other traditional file systems, namely, Ext2, Ext3, XFS, JFS, and ReiserFS. The experiments carried out prove, for the first time, that a new file system design based on separation of data and metadata can significantly improve file systems' performance without requiring several storage devices.

Many parallel applications involve different independent tasks with their own data. Using the MPMD model, programmers can have a modular view and simplified structure of the parallel programs. Although MPI supports both SPMD and MPMD models for programming, MPI libraries do not provide an efficient way for task communication for the MPMD model. We have developed a programming environment, called ClusterGOP, for building and developing parallel applications. Based on the graph-oriented programming (GOP) model, ClusterGOP provides higher-level abstractions for message-passing parallel programming with the support of software tools for developing and running parallel applications. In this paper, we describe how ClusterGOP supports programming of MPMD parallel applications on top of MPI. We discuss the issues of implementing the MPMD model in ClusterGOP using MPI and evaluate the performance by using example applications.

Graph data in large scientific/engineering applications are often too massive to fit inside the computer's main memory. The resulting input/output (I/O) costs could be a major performance bottleneck. This paper proposes an extension to extant multilevel graph partitioning algorithms with improved I/O-efficiency. The input graph is envisioned as the union of disjoint blocks (subgraphs) of almost the same size. Each block is coarsened in turn. Recursive matching and contraction are the operations in this phase. All the coarsened blocks are then merged in an iterative manner in order to ensure that the resulting graph fits in the main memory. This graph is then treated with an in-core multilevel graph partitioning algorithm in the usual way. Our experimental results show that the larger graph size is, the more dependent on the I/O-efficiency the performance is. And our modification can easily partition very large graphs. It also exhibits considerable improvement in I/O-complexity.

This paper shows how to use sticker to construct solution space of DNA for the library sequences in the set-packing problem and the clique problem. Then, with biological operations, we propose DNA-based algorithms to remove illegal solutions and to find legal solutions for the set-packing and clique problems from the solution space of sticker. Any NP-complete problem in Cook's Theorem can be reduced and solved by the proposed DNA-based computing approach if its size is equal to or less than that of the set-packing problem. Otherwise, Cook's Theorem is incorrect on DNA-based computing and a new DNA algorithm should be developed from the characteristics of the NP-complete problem. Finally, the result to DNA simulation is given.

In this paper, we perform some experiments to show that the quantization noise caused by low-bit-rate speech coding can be characterized as a white noise process. Then, the signal-to-quantization noise ratio of the decoded speech for a given bit-rate is estimated by observing the perceptual speech quality equivalent to the artificially generated noisy speech obtained by adding a white Gaussian noise source. This information is incorporated into the parameter tuning of a noise-robust compensation algorithm for speech recognition so that the compensation algorithm can be performed better under a range of the estimated SNRs. Finally, we apply the compensation algorithm to a connected digit string recognition system that utilizes speech signals decoded by the GSM adaptive multi-rate (AMR) speech coder. It is shown that the noise-robust compensation algorithm reduces word error rates by 15% or more at low bit-rate modes of the AMR speech coder.

This study was conducted to examine the relationship between technostress - techno-centered tendency- and antisocial behavior on computers. Questionnaire data of computer operators were analyzed by multivariate-analysis. The results of the analysis indicated that high techno-centered tendency has a strong relationship with antisocial behavior on computers. Among the component factors of techno-centered tendency, absorption in operating computers was proven to have the strongest association with antisocial behavior on computers.

In this paper we propose a parallel and distributed computation of genetic local search with irregular topology in distributed environments. The scheme we propose in this paper is implemented with a tree topology established on an irregular network where each computing element carries out genetic local search on its own chromosome set and communicates with its parent when the best solution of each generation is updated. We evaluate the proposed algorithm by a simulation system implemented on a PC-cluster. We test our algorithm on four types topologies: star, line, balanced binary tree and sided binary tree, and investigate the influence of communication topology and delay on the evolution process.

Providing workflow function is one of the most important research issues in the next generation Internet services such as Web Service and Grid Computing. Scalability for Internet scale services, reliability for unstable Internet resources, and management functions of workflow systems are the essential requirements in these environments. However, existing workflow enactment models for enterprises could not meet these requirements. This paper proposes the PeerFlow that is a P2P based workflow enactment model, to provide workflow functions for the next generation Internet services. To apply P2P model to the workflow enactment model, we introduce the concept of the instance buddy and the index data of workflow instances, then propose the principle architecture of the PeerFlow. The instance buddy enables the autonomous processing of peers, and it is used for recovery and monitoring functions. This paper also presents the recovery capabilities of PeerFlow with formal proofs for the reliability issues and a performance evaluation with SimPy, the Python simulation package.

This paper presents a network architecture with a dual interface IP handoff technique that allows smooth node mobility without using any intermediate proxy. The proposed architecture is suitable for low bit-rate time sensitive real time applications, where payload tends to be short and packet header overhead is particularly significant. Connections are established as per permanent addresses of the nodes but are carried on by the IP layer according to the temporary addresses by address translation within the end hosts. The mapping information is maintained by database servers, which can be placed in the Internet in a distributed manner. We describe the architecture and show its mobile capabilities by prototype implementation and performance evaluation. Furthermore a dual-interface handoff suitable to the proposed architecture is also introduced. Preliminary results show that the proposed architecture has significantly low overheads. It is compatible with the existing infrastructure and works fine in both IPv4 and IPv6 environments. Analysis also shows that with dual-interface handoff it is possible to achieve seamless handoff without any packet loss by exploiting overlapping coverage area and speed of the mobile node. Handoff latency is reduced significantly as compare to MIPv6. We believe that with more powerful network interface card drivers our concept of dual interface handoff can be realized.

The proposed comparator includes high gain preamplifier with a new swing limiter. It is shown that, for a given unity gain bandwidth, the high gain preamplifier of high output impedance can be made faster than the low gain one if properly combined with a high-speed low-level swing limiter.

Multi-Carrier Code Division Multiple Access (MC-CDMA) is one of candidates for the next generation wireless communication systems. In an uplink, the MC-CDMA system suffers from the different access timing (asynchronous transmission), the different fading, and the different frequency offsets of each active user. In this paper we analyze the effects of the frequency offset compensation with MMSE-MUD (minimum mean square error based multi-user detection) for MC-CDMA in a quasi-synchronous uplink. We consider the MC-CDMA system with two subcarrier mapping schemes, the continuous mapping scheme and the discrete mapping scheme. From our theoretical analysis and computer simulation, we show that the MMSE-MUD can compensate the different frequency offsets among users. We also show that the MMSE-MUD significantly improves the bit error rate (BER) for the MC-CDMA system with the continuous mapping scheme.