A Class of Parallel Tiled Linear Algebra Algorithms for Multicore Architectures

As multicore systems continue to gain ground in the High Performance Computing world, linear algebra algorithms have to be reformulated or new algorithms have to be developed in order to take advantage of the architectural features on these new processors. Fine grain parallelism becomes a major requirement and introduces the necessity of loose synchronization in the parallel execution of an operation. This paper presents an algorithm for the Cholesky, LU and QR factorization where the operations can be represented as a sequence of small tasks that operate on square blocks of data. These tasks can be dynamically scheduled for execution based on the dependencies among them and on the availability of computational resources. This may result in an out of order execution of the tasks which will completely hide the presence of intrinsically sequential tasks in the factorization. Performance comparisons are presented with the LAPACK algorithms where parallelism can only be exploited at the level of the BLAS operations and vendor implementations

Time and information in perceptual adaptation to speech

Presubmission manuscript and supplementary files (stimuli, stimulus presentation code, data, data analysis code).Perceptual adaptation to a talker enables listeners to efficiently resolve the many-to-many mapping between variable speech acoustics and abstract linguistic representations. However, models of speech perception have not delved into the variety or the quantity of information necessary for successful adaptation, nor how adaptation unfolds over time. In three experiments using speeded classification of spoken words, we explored how the quantity (duration), quality (phonetic detail), and temporal continuity of talker-specific context contribute to facilitating perceptual adaptation to speech. In single- and mixed-talker conditions, listeners identified phonetically-confusable target words in isolation or preceded by carrier phrases of varying lengths and phonetic content, spoken by the same talker as the target word. Word identification was always slower in mixed-talker conditions than single-talker ones. However, interference from talker variability decreased as the duration of preceding speech increased but was not affected by the amount of preceding talker-specific phonetic information. Furthermore, efficiency gains from adaptation depended on temporal continuity between preceding speech and the target word. These results suggest that perceptual adaptation to speech may be understood via models of auditory streaming, where perceptual continuity of an auditory object (e.g., a talker) facilitates allocation of attentional resources, resulting in more efficient perceptual processing.NIH NIDCD (R03DC014045

A mathematical model for dynamic memory networks

The aim of this paper is to bring together the work done several years ago by M.A. Fiol and the other authors to formulate a quite general mathematical model for a kind of permutation networks known as dynamic memories. A dynamic memory is constituted by an array of cells, each storing one datum, and an interconnection network between the cells that allows the constant circulation of the stored data. The objective is to design the interconnection network in order to have short access time and a simple memory control. We review how most of the proposals of dynamic memories that have appeared in the literature fit in this general model, and how it can be used to design new structures with good access properties. Moreover, using the idea of projecting a digraph onto a de Bruijn digraph, we propose new structures for dynamic memories with vectorial capabilities. Some of these new proposals are based on iterated line digraphs, which have been widely and successfully used by M.A. Fiol and his coauthors to solve many different problems in graph theory.Peer Reviewe

Aluminum Oxide Layers as Possible Components for Layered Tunnel Barriers

We have studied transport properties of Nb/Al/AlOx/Nb tunnel junctions with ultrathin aluminum oxide layers formed by (i) thermal oxidation and (ii) plasma oxidation, before and after rapid thermal post-annealing of the completed structures at temperatures up to 550 deg C. Post-annealing at temperatures above 300 deg C results in a significant decrease of the tunneling conductance of thermally-grown barriers, while plasma-grown barriers start to change only at annealing temperatures above 450 deg C. Fitting the experimental I-V curves of the junctions using the results of the microscopic theory of direct tunneling shows that the annealing of thermally-grown oxides at temperatures above 300 deg C results in a substantial increase of their average tunnel barriers height, from ~1.8 eV to ~2.45 eV, versus the practically unchanged height of ~2.0 eV for plasma-grown layers. This difference, together with high endurance of annealed barriers under electric stress (breakdown field above 10 MV/cm) may enable all-AlOx and SiO2/AlOx layered "crested" barriers for advanced floating-gate memory applications.Comment: 7 pages, 6 figure

From Parallel Sequence Representations to Calligraphic Control: A Conspiracy of Neural Circuits

Calligraphic writing presents a rich set of challenges to the human movement control system. These challenges include: initial learning, and recall from memory, of prescribed stroke sequences; critical timing of stroke onsets and durations; fine control of grip and contact forces; and letter-form invariance under voluntary size scaling, which entails fine control of stroke direction and amplitude during recruitment and derecruitment of musculoskeletal degrees of freedom. Experimental and computational studies in behavioral neuroscience have made rapid progress toward explaining the learning, planning and contTOl exercised in tasks that share features with calligraphic writing and drawing. This article summarizes computational neuroscience models and related neurobiological data that reveal critical operations spanning from parallel sequence representations to fine force control. Part one addresses stroke sequencing. It treats competitive queuing (CQ) models of sequence representation, performance, learning, and recall. Part two addresses letter size scaling and motor equivalence. It treats cursive handwriting models together with models in which sensory-motor tmnsformations are performed by circuits that learn inverse differential kinematic mappings. Part three addresses fine-grained control of timing and transient forces, by treating circuit models that learn to solve inverse dynamics problems.National Institutes of Health (R01 DC02852