Showing papers by "IBM published in 2005"

The Design and Implementation of FFTW3

Abstract: FFTW is an implementation of the discrete Fourier transform (DFT) that adapts to the hardware in order to maximize performance. This paper shows that such an approach can yield an implementation that is competitive with hand-optimized libraries, and describes the software structure that makes our current FFTW3 version flexible and adaptive. We further discuss a new algorithm for real-data DFTs of prime size, a new way of implementing DFTs by means of machine-specific single-instruction, multiple-data (SIMD) instructions, and how a special-purpose compiler can derive optimized implementations of the discrete cosine and sine transforms automatically from a DFT algorithm.

Sparsity and smoothness via the fused lasso

Abstract: Summary. The lasso penalizes a least squares regression by the sum of the absolute values (L1-norm) of the coefficients. The form of this penalty encourages sparse solutions (with many coefficients equal to 0). We propose the ‘fused lasso’, a generalization that is designed for problems with features that can be ordered in some meaningful way. The fused lasso penalizes the L1-norm of both the coefficients and their successive differences. Thus it encourages sparsity of the coefficients and also sparsity of their differences—i.e. local constancy of the coefficient profile. The fused lasso is especially useful when the number of features p is much greater than N, the sample size. The technique is also extended to the ‘hinge’ loss function that underlies the support vector classifier.We illustrate the methods on examples from protein mass spectroscopy and gene expression data.

Localization via ultra-wideband radios: a look at positioning aspects for future sensor networks

Abstract: UWB technology provides an excellent means for wireless positioning due to its high resolution capability in the time domain. Its ability to resolve multipath components makes it possible to obtain accurate location estimates without the need for complex estimation algorithms. In this article, theoretical limits for TOA estimation and TOA-based location estimation for UWB systems have been considered. Due to the complexity of the optimal schemes, suboptimal but practical alternatives have been emphasized. Performance limits for hybrid TOA/SS and TDOA/SS schemes have also been considered. Although the fundamental mechanisms for localization, including AOA-, TOA-, TDOA-, and SS-based methods, apply to all radio air interface, some positioning techniques are favored by UWB-based systems using ultrawide bandwidths.

PbSe Nanocrystal Solids for n- and p-Channel Thin Film Field-Effect Transistors

Abstract: Initially poorly conducting PbSe nanocrystal solids (quantum dot arrays or superlattices) can be chemically "activated" to fabricate n- and p-channel field effect transistors with electron and hole mobilities of 0.9 and 0.2 square centimeters per volt-second, respectively; with current modulations of about 10(3) to 10(4); and with current density approaching 3 x 10(4) amperes per square centimeter. Chemical treatments engineer the interparticle spacing, electronic coupling, and doping while passivating electronic traps. These nanocrystal field-effect transistors allow reversible switching between n- and p-transport, providing options for complementary metal oxide semiconductor circuits and enabling a range of low-cost, large-area electronic, optoelectronic, thermoelectric, and sensing applications.

Scale-Free Brain Functional Networks

Abstract: Functional magnetic resonance imaging is used to extract functional networks connecting correlated human brain sites. Analysis of the resulting networks in different tasks shows that (a) the distribution of functional connections, and the probability of finding a link versus distance are both scale-free, (b) the characteristic path length is small and comparable with those of equivalent random networks, and (c) the clustering coefficient is orders of magnitude larger than those of equivalent random networks. All these properties, typical of scale-free small-world networks, reflect important functional information about brain states.

Regular and irregular progressive edge-growth tanner graphs

Abstract: We propose a general method for constructing Tanner graphs having a large girth by establishing edges or connections between symbol and check nodes in an edge-by-edge manner, called progressive edge-growth (PEG) algorithm. Lower bounds on the girth of PEG Tanner graphs and on the minimum distance of the resulting low-density parity-check (LDPC) codes are derived in terms of parameters of the graphs. Simple variations of the PEG algorithm can also be applied to generate linear-time encodeable LDPC codes. Regular and irregular LDPC codes using PEG Tanner graphs and allowing symbol nodes to take values over GF(q) (q>2) are investigated. Simulation results show that the PEG algorithm is a powerful algorithm to generate good short-block-length LDPC codes.

X10: an object-oriented approach to non-uniform cluster computing

Abstract: It is now well established that the device scaling predicted by Moore's Law is no longer a viable option for increasing the clock frequency of future uniprocessor systems at the rate that had been sustained during the last two decades. As a result, future systems are rapidly moving from uniprocessor to multiprocessor configurations, so as to use parallelism instead of frequency scaling as the foundation for increased compute capacity. The dominant emerging multiprocessor structure for the future is a Non-Uniform Cluster Computing (NUCC) system with nodes that are built out of multi-core SMP chips with non-uniform memory hierarchies, and interconnected in horizontally scalable cluster configurations such as blade servers. Unlike previous generations of hardware evolution, this shift will have a major impact on existing software. Current OO language facilities for concurrent and distributed programming are inadequate for addressing the needs of NUCC systems because they do not support the notions of non-uniform data access within a node, or of tight coupling of distributed nodes.We have designed a modern object-oriented programming language, X10, for high performance, high productivity programming of NUCC systems. A member of the partitioned global address space family of languages, X10 highlights the explicit reification of locality in the form of places}; lightweight activities embodied in async, future, foreach, and ateach constructs; a construct for termination detection (finish); the use of lock-free synchronization (atomic blocks); and the manipulation of cluster-wide global data structures. We present an overview of the X10 programming model and language, experience with our reference implementation, and results from some initial productivity comparisons between the X10 and Java™ languages.

Reverse engineering of regulatory networks in human B cells.

Abstract: Cellular phenotypes are determined by the differential activity of networks linking coregulated genes. Available methods for the reverse engineering of such networks from genome-wide expression profiles have been successful only in the analysis of lower eukaryotes with simple genomes. Using a new method called ARACNe (algorithm for the reconstruction of accurate cellular networks), we report the reconstruction of regulatory networks from expression profiles of human B cells. The results are suggestive a hierarchical, scale-free network, where a few highly interconnected genes (hubs) account for most of the interactions. Validation of the network against available data led to the identification of MYC as a major hub, which controls a network comprising known target genes as well as new ones, which were biochemically validated. The newly identified MYC targets include some major hubs. This approach can be generally useful for the analysis of normal and pathologic networks in mammalian cells.

Active control of slow light on a chip with photonic crystal waveguides

Abstract: It is known that light can be slowed down in dispersive materials near resonances. Dramatic reduction of the light group velocity-and even bringing light pulses to a complete halt-has been demonstrated recently in various atomic and solid state systems, where the material absorption is cancelled via quantum optical coherent effects. Exploitation of slow light phenomena has potential for applications ranging from all-optical storage to all-optical switching. Existing schemes, however, are restricted to the narrow frequency range of the material resonance, which limits the operation frequency, maximum data rate and storage capacity. Moreover, the implementation of external lasers, low pressures and/or low temperatures prevents miniaturization and hinders practical applications. Here we experimentally demonstrate an over 300-fold reduction of the group velocity on a silicon chip via an ultra-compact photonic integrated circuit using low-loss silicon photonic crystal waveguides that can support an optical mode with a submicrometre cross-section. In addition, we show fast (approximately 100 ns) and efficient (2 mW electric power) active control of the group velocity by localized heating of the photonic crystal waveguide with an integrated micro-heater.

Data privacy through optimal k-anonymization

Abstract: Data de-identification reconciles the demand for release of data for research purposes and the demand for privacy from individuals. This paper proposes and evaluates an optimization algorithm for the powerful de-identification procedure known as k-anonymization. A k-anonymized dataset has the property that each record is indistinguishable from at least k - 1 others. Even simple restrictions of optimized k-anonymity are NP-hard, leading to significant computational challenges. We present a new approach to exploring the space of possible anonymizations that tames the combinatorics of the problem, and develop data-management strategies to reduce reliance on expensive operations such as sorting. Through experiments on real census data, we show the resulting algorithm can find optimal k-anonymizations under two representative cost measures and a wide range of k. We also show that the algorithm can produce good anonymizations in circumstances where the input data or input parameters preclude finding an optimal solution in reasonable time. Finally, we use the algorithm to explore the effects of different coding approaches and problem variations on anonymization quality and performance. To our knowledge, this is the first result demonstrating optimal k-anonymization of a non-trivial dataset under a general model of the problem.

Designing PbSe Nanowires and Nanorings through Oriented Attachment of Nanoparticles

Abstract: Single-crystal PbSe nanowires are synthesized in solution through oriented attachment of nanocrystal building blocks. Reaction temperatures of 190-250 degrees C and multicomponent surfactant mixtures result in a nearly defect-free crystal lattice and high uniformity of nanowire diameter along the entire length. The wires' dimensions are tuned by tailoring reaction conditions in a range from approximately 4 to approximately 20 nm in diameter with wire lengths up to approximately 30 microm. PbSe nanocrystals bind to each other on either {100}, {110}, or {111} faces, depending on the surfactant molecules present in the reaction solution. While PbSe nanocrystals have the centrosymmetric rocksalt lattice, they can lack central symmetry due to a noncentrosymmetric arrangement of Pb- and Se-terminated {111} facets and possess dipole driving one-dimensional oriented attachment of nanocrystals to form nanowires. In addition to straight nanowires, zigzag, helical, branched, and tapered nanowires as well as single-crystal nanorings can be controllably prepared in one-pot reactions by careful adjustment of the reaction conditions.

Dumbbell-like Bifunctional Au−Fe3O4 Nanoparticles

Abstract: Dumbbell-like Au−Fe3O4 nanoparticles are synthesized using decomposition of Fe(CO)5 on the surface of the Au nanoparticles followed by oxidation in 1-octadecene solvent. The size of the particles is tuned from 2 to 8 nm for Au and 4 nm to 20 nm for Fe3O4. The particles show the characteristic surface plasmon absorption of Au and the magnetic properties of Fe3O4 that are affected by the interactions between Au and Fe3O4. The dumbbell is formed through epitaxial growth of iron oxide on the Au seeds, and the growth can be affected by the polarity of the solvent, as the use of diphenyl ether results in flower-like Au−Fe3O4 nanoparticles.

Introduction to the cell multiprocessor

Abstract: This paper provides an introductory overview of the Cell multiprocessor. Cell represents a revolutionary extension of conventional microprocessor architecture and organization. The paper discusses the history of the project, the program objectives and challenges, the disign concept, the architecture and programming models, and the implementation.

Reduced-complexity decoding of LDPC codes

Abstract: Various log-likelihood-ratio-based belief-propagation (LLR-BP) decoding algorithms and their reduced-complexity derivatives for low-density parity-check (LDPC) codes are presented. Numerically accurate representations of the check-node update computation used in LLR-BP decoding are described. Furthermore, approximate representations of the decoding computations are shown to achieve a reduction in complexity by simplifying the check-node update, or symbol-node update, or both. In particular, two main approaches for simplified check-node updates are presented that are based on the so-called min-sum approximation coupled with either a normalization term or an additive offset term. Density evolution is used to analyze the performance of these decoding algorithms, to determine the optimum values of the key parameters, and to evaluate finite quantization effects. Simulation results show that these reduced-complexity decoding algorithms for LDPC codes achieve a performance very close to that of the BP algorithm. The unified treatment of decoding techniques for LDPC codes presented here provides flexibility in selecting the appropriate scheme from performance, latency, computational-complexity, and memory-requirement perspectives.

The private classical capacity and quantum capacity of a quantum channel

Abstract: A formula for the capacity of a quantum channel for transmitting private classical information is derived. This is shown to be equal to the capacity of the channel for generating a secret key, and neither capacity is enhanced by forward public classical communication. Motivated by the work of Schumacher and Westmoreland on quantum privacy and quantum coherence, parallels between private classical information and quantum information are exploited to obtain an expression for the capacity of a quantum channel for generating pure bipartite entanglement. The latter implies a new proof of the quantum channel coding theorem and a simple proof of the converse. The coherent information plays a role in all of the above mentioned capacities

Overview of the HUPO Plasma Proteome Project: results from the pilot phase with 35 collaborating laboratories and multiple analytical groups, generating a core dataset of 3020 proteins and a publicly-available database.

Abstract: HUPO initiated the Plasma Proteome Project (PPP) in 2002. Its pilot phase has (1) evaluated advantages and limitations of many depletion, fractionation, and MS technology platforms; (2) compared PPP reference specimens of human serum and EDTA, heparin, and citrate-anti-coagulated plasma; and (3) created a publicly-available knowledge base (www.bioinformatics.med.umich.edu/hupo/ppp; www.ebi.ac.uk/pride). Thirty-five participating laboratories in 13 countries submitted datasets. Working groups addressed (a) specimen stability and protein concentrations; (b) protein identifications from 18 MS/MS datasets; (c) independent analyses from raw MS-MS spectra; (d) search engine performance, subproteome analyses, and biological insights; (e) antibody arrays; and (f) direct MS/SELDI analyses. MS-MS datasets had 15 710 different International Protein Index (IPI) protein IDs; our integration algorithm applied to multiple matches of peptide sequences yielded 9504 IPI proteins identified with one or more peptides and 3020 proteins identified with two or more peptides (the Core Dataset). These proteins have been characterized with Gene Ontology, InterPro, Novartis Atlas, OMIM, and immunoassay-based concentration determinations. The database permits examination of many other subsets, such as 1274 proteins identified with three or more peptides. Reverse protein to DNA matching identified proteins for 118 previously unidentified ORFs. We recommend use of plasma instead of serum, with EDTA (or citrate) for anticoagulation. To improve resolution, sensitivity and reproducibility of peptide identifications and protein matches, we recommend combinations of depletion, fractionation, and MS/MS technologies, with explicit criteria for evaluation of spectra, use of search algorithms, and integration of homologous protein matches. This Special Issue of PROTEOMICS presents papers integral to the collaborative analysis plus many reports of supplementary work on various aspects of the PPP workplan. These PPP results on complexity, dynamic range, incomplete sampling, false-positive matches, and integration of diverse datasets for plasma and serum proteins lay a foundation for development and validation of circulating protein biomarkers in health and disease.

Distillation of secret key and entanglement from quantum states

Abstract: We study and solve the problem of distilling a secret key from quantum states representing correlation between two parties (Alice and Bob) and an eavesdropper (Eve) via oneway public discussion: we...

HMQV: a high-performance secure diffie-hellman protocol

Abstract: The MQV protocol of Law, Menezes, Qu, Solinas and Vanstone is possibly the most efficient of all known authenticated Diffie-Hellman protocols that use public-key authentication. In addition to great performance, the protocol has been designed to achieve a remarkable list of security properties. As a result MQV has been widely standardized, and has recently been chosen by the NSA as the key exchange mechanism underlying “the next generation cryptography to protect US government information”. One question that has not been settled so far is whether the protocol can be proven secure in a rigorous model of key-exchange security. In order to provide an answer to this question we analyze the MQV protocol in the Canetti-Krawczyk model of key exchange. Unfortunately, we show that MQV fails to a variety of attacks in this model that invalidate its basic security as well as many of its stated security goals. On the basis of these findings, we present HMQV, a carefully designed variant of MQV, that provides the same superb performance and functionality of the original protocol but for which all the MQV's security goals can be formally proved to hold in the random oracle model under the computational Diffie-Hellman assumption. We base the design and proof of HMQV on a new form of “challenge-response signatures”, derived from the Schnorr identification scheme, that have the property that both the challenger and signer can compute the same signature; the former by having chosen the challenge and the latter by knowing the private signature key.

Molecules on insulating films: scanning-tunneling microscopy imaging of individual molecular orbitals.

Abstract: Ultrathin insulating NaCl films have been employed to decouple individual pentacene molecules electronically from the metallic substrate. This allows the inherent electronic structure of the free molecule to be preserved and studied by means of low-temperature scanning-tunneling microscopy. Thereby direct images of the unperturbed molecular orbitals of the individual pentacene molecules are obtained. Elastic scattering quantum chemistry calculations substantiate the experimental findings.

The Role of Metal-Nanotube Contact in the Performance of Carbon Nanotube Field-Effect Transistors

Abstract: Single-wall carbon nanotube field-effect transistors (CNFETs) have been shown to behave as Schottky barrier (SB) devices. It is not clear, however, what factors control the SB size. Here we present the first statistical analysis of this issue. We show that a large data set of more than 100 devices can be consistently accounted by a model that relates the on-current of a CNFET to a tunneling barrier whose height is determined by the nanotube diameter and the nature of the source/drain metal contacts. Our study permits identification of the desired combination of tube diameter and type of metal that provides the optimum performance of a CNFET.

On k -anonymity and the curse of dimensionality

Abstract: In recent years, the wide availability of personal data has made the problem of privacy preserving data mining an important one. A number of methods have recently been proposed for privacy preserving data mining of multidimensional data records. One of the methods for privacy preserving data mining is that of anonymization, in which a record is released only if it is indistinguishable from k other entities in the data. We note that methods such as k-anonymity are highly dependent upon spatial locality in order to effectively implement the technique in a statistically robust way. In high dimensional space the data becomes sparse, and the concept of spatial locality is no longer easy to define from an application point of view. In this paper, we view the k-anonymization problem from the perspective of inference attacks over all possible combinations of attributes. We show that when the data contains a large number of attributes which may be considered quasi-identifiers, it becomes difficult to anonymize the data without an unacceptably high amount of information loss. This is because an exponential number of combinations of dimensions can be used to make precise inference attacks, even when individual attributes are partially specified within a range. We provide an analysis of the effect of dimensionality on k-anonymity methods. We conclude that when a data set contains a large number of attributes which are open to inference attacks, we are faced with a choice of either completely suppressing most of the data or losing the desired level of anonymity. Thus, this paper shows that the curse of high dimensionality also applies to the problem of privacy preserving data mining.

The architecture of virtual machines

Abstract: A virtual machine can support individual processes or a complete system depending on the abstraction level where virtualization occurs. Some VMs support flexible hardware usage and software isolation, while others translate from one instruction set to another. Virtualizing a system or component -such as a processor, memory, or an I/O device - at a given abstraction level maps its interface and visible resources onto the interface and resources of an underlying, possibly different, real system. Consequently, the real system appears as a different virtual system or even as multiple virtual systems. Interjecting virtualizing software between abstraction layers near the HW/SW interface forms a virtual machine that allows otherwise incompatible subsystems to work together. Further, replication by virtualization enables more flexible and efficient and efficient use of hardware resources.

Stable SRAM cell design for the 32 nm node and beyond

Abstract: SRAM cell stability will be a primary concern for future technologies due to variability and decreasing power supply voltages. 6T-SRAM can be optimized for stability by choosing the cell layout, device threshold voltages, and the /spl beta/ ratio. 8T-SRAM, however, provides a much greater enhancement in stability by eliminating cell disturbs during a read access, thus facilitating continued technology scaling. We demonstrate the smallest 6T (0.124/spl mu/m/sup 2/ half-cell) and full 8T (0.1998/spl mu/m/sup 2/) cells to date.

An analytical model for multi-tier internet services and its applications

Abstract: Since many Internet applications employ a multi-tier architecture, in this paper, we focus on the problem of analytically modeling the behavior of such applications. We present a model based on a network of queues, where the queues represent different tiers of the application. Our model is sufficiently general to capture (i) the behavior of tiers with significantly different performance characteristics and (ii) application idiosyncrasies such as session-based workloads, concurrency limits, and caching at intermediate tiers. We validate our model using real multi-tier applications running on a Linux server cluster. Our experiments indicate that our model faithfully captures the performance of these applications for a number of workloads and configurations. For a variety of scenarios, including those with caching at one of the application tiers, the average response times predicted by our model were within the 95% confidence intervals of the observed average response times. Our experiments also demonstrate the utility of the model for dynamic capacity provisioning, performance prediction, bottleneck identification, and session policing. In one scenario, where the request arrival rate increased from less than 1500 to nearly 4200 requests/min, a dynamic provisioning technique employing our model was able to maintain response time targets by increasing the capacity of two of the application tiers by factors of 2 and 3.5, respectively.

The design and implementation of a first-generation CELL processor

Abstract: A CELL processor is a multi-core chip consisting of a 64b power architecture processor, multiple streaming processors, a flexible IO interface, and a memory interface controller This SoC is implemented in 90nm SOI technology The chip is designed with a high degree of modularity and reuse to maximize the custom circuit content and achieve a high-frequency clock-rate

Web Service Semantics - WSDL-S

Abstract: The current WSDL standard operates at the syntactic level and lacks the semantic expressivity needed to represent the requirements and capabilities of Web Services. Semantics can improve software reuse and discovery, significantly facilitate composition of Web services and enable integrating legacy applications as part of business process integration. The Web Service Semantics technical note defines a mechanism to associate semantic annotations with Web services that are described using Web Service Description Language (WSDL). It is conceptually based on, but a significant refinement in details of, the original WSDL-S proposal [WSDL-S] from the LSDIS laboratory at the University of Georgia. In this proposal, we assume that formal semantic models relevant to the services already exist. In our approach, these models are maintained outside of WSDL documents and are referenced from the WSDL document via WSDL extensibility elements. The type of semantic information that would be useful in describing a Web Service encompass the concepts defined by the semantic Web community in OWL-S [OWL-S] and other efforts [METEOR-S, WSMO]. The semantic information specified in this document includes definitions of the precondition, input, output and effects of Web service operations. This approach offers multiple advantages over OWL-S. First, users can describe, in an upwardly compatible way, both the semantics and operation level details in WSDLa language that the developer community is familiar with. Secondly, by externalizing the semantic domain models, we take an agnostic approach to ontology representation languages. This allows Web service developers to annotate their Web services with their choice of ontology language (such as UML or OWL) unlike in OWL-S. This is significant because the ability to reuse existing domain models expressed in modeling languages like UML can greatly alleviate the need to separately model semantics. Finally, it is relatively easy to update the existing tooling around WSDL specification to accommodate our incremental approach. Status This is a technical note provided for discussion purposes and to elicit feedback on approaches to adding semantics to Web services descriptions. Table of

On Coreference Resolution Performance Metrics

Abstract: The paper proposes a Constrained Entity-Alignment F-Measure (CEAF) for evaluating coreference resolution. The metric is computed by aligning reference and system entities (or coreference chains) with the constraint that a system (reference) entity is aligned with at most one reference (system) entity. We show that the best alignment is a maximum bipartite matching problem which can be solved by the Kuhn-Munkres algorithm. Comparative experiments are conducted to show that the widely-known MUC F-measure has serious flaws in evaluating a coreference system. The proposed metric is also compared with the ACE-Value, the official evaluation metric in the Automatic Content Extraction (ACE) task, and we conclude that the proposed metric possesses some properties such as symmetry and better interpretability missing in the ACE-Value.

Evaluation of Large-Eddy Simulations via Observations of Nocturnal Marine Stratocumulus

Abstract: Data from the first research flight (RF01) of the second Dynamics and Chemistry of Marine Stratocumulus (DYCOMS-II) field study are used to evaluate the fidelity with which large-eddy simulations (LESs) can represent the turbulent structure of stratocumulus-topped boundary layers. The initial data and forcings for this case placed it in an interesting part of parameter space, near the boundary where cloud-top mixing is thought to render the cloud layer unstable on the one hand, or tending toward a decoupled structure on the other hand. The basis of this evaluation consists of sixteen 4-h simulations from 10 modeling centers over grids whose vertical spacing wa s5ma t thecloud-top interface and whose horizontal spacing was 35 m. Extensive sensitivity studies of both the configuration of the case and the numerical setup also enhanced the analysis. Overall it was found that (i) if efforts are made to reduce spurious mixing at cloud top, either by refining the vertical grid or limiting the effects of the subgrid model in this region, then the observed turbulent and thermodynamic structure of the layer can be reproduced with some fidelity; (ii) the base, or native configuration of most simulations greatly overestimated mixing at cloud top, tending toward a decoupled layer in which cloud liquid water path and turbulent intensities were grossly underestimated; (iii) the sensitivity of the simulations to the representation of mixing at cloud top is, to a certain extent, amplified by particulars of this case. Overall the results suggest that the use of LESs to map out the behavior of the stratocumulus-topped boundary layer in this interesting region of parameter space requires a more compelling representation of processes at cloud top. In the absence of significant leaps in the understanding of subgrid-scale (SGS) physics, such a representation can only be achieved by a significant refinement in resolution—a refinement that, while conceivable given existing resources, is probably still beyond the reach of most centers.