Accounting for Memory Bank Contention and Delay in High-Bandwidth Multiprocessors

This paper considers issues of memory performance in shared memory multiprocessors that provide a high-bandwidth network and in which the memory banks are slower than the processors. We are concerned with the effects of memory bank contention, memory bank delay, and the bank expansion factor (the ratio of number of banks to number of processors) on performance, particularly for irregular memory access patterns. This work was motivated by observed discrepancies between predicted and actual performance in a number of irregular algorithms implemented for the cray C90 when the memory contention at a particular location is high. We develop a formal framework for studying memory bank contention and delay, and show several results, both experimental and theoretical. We first show experimentally that our framework is a good predictor of performance on the cray C90 and J90, providing a good accounting of bank contention and delay. Second, we show that it often improves performance to have addi..

Analyses of associations between three positionally cloned asthma candidate genes and asthma or asthma-related phenotypes in a Chinese population

<p>Abstract</p> <p>Background</p> <p>Six asthma candidate genes, ADAM33, NPSR1, PHF11, DPP10, HLA-G, and CYFIP2, located at different chromosome regions have been positionally cloned following the reported linkage studies. For ADAM33, NPSR1, and CYFIP2, the associations with asthma or asthma-related phenotypes have been studied in East Asian populations such as Chinese and Japanese. However, for PHF11, DPP10, and HLA-G, none of the association studies have been conducted in Asian populations. Therefore, the aim of the present study is to test the associations between these three positionally cloned genes and asthma or asthma-related phenotypes in a Chinese population.</p> <p>Methods</p> <p>Two, five, and two single nucleotide polymorphisms (SNPs) in the identified top regions of PHF11, DPP10, and HLA-G, respectively, were genotyped in 1183 independent samples. The study samples were selected based on asthma affectation status and extreme values in at least one of the following three asthma-related phenotypes: total serum immunoglobulin E levels, bronchial responsiveness test, and skin prick test. Both single SNP and haplotype analyses were performed.</p> <p>Results</p> <p>We found that DPP10 was significantly associated with bronchial hyperresponsiveness (BHR) and BHR asthma after the adjustment for multiple testing; while the associations of PHF11 with positive skin reactions to antigens and the associations of HLA-G with BHR asthma were only nominally significant.</p> <p>Conclusion</p> <p>Our study is the first one to provide additional evidence that supports the roles of DPP10 in influencing asthma or BHR in a Chinese population.</p

A theory of how active behavior stabilises neural activity: neural gain modulation by closed-loop environmental feedback

During active behaviours like running, swimming, whisking or sniffing, motor actions shape sensory input and sensory percepts guide future motor commands. Ongoing cycles of sensory and motor processing constitute a closed-loop feedback system which is central to motor control and, it has been argued, for perceptual processes. This closed-loop feedback is mediated by brainwide neural circuits but how the presence of feedback signals impacts on the dynamics and function of neurons is not well understood. Here we present a simple theory suggesting that closed-loop feedback between the brain/body/environment can modulate neural gain and, consequently, change endogenous neural fluctuations and responses to sensory input. We support this theory with modeling and data analysis in two vertebrate systems. First, in a model of rodent whisking we show that negative feedback mediated by whisking vibrissa can suppress coherent neural fluctuations and neural responses to sensory input in the barrel cortex. We argue this suppression provides an appealing account of a brain state transition (a marked change in global brain activity) coincident with the onset of whisking in rodents. Moreover, this mechanism suggests a novel signal detection mechanism that selectively accentuates active, rather than passive, whisker touch signals. This mechanism is consistent with a predictive coding strategy that is sensitive to the consequences of motor actions rather than the difference between the predicted and actual sensory input. We further support the theory by re-analysing previously published two-photon data recorded in zebrafish larvae performing closed-loop optomotor behaviour in a virtual swim simulator. We show, as predicted by this theory, that the degree to which each cell contributes in linking sensory and motor signals well explains how much its neural fluctuations are suppressed by closed-loop optomotor behaviour. More generally we argue that our results demonstrate the dependence of neural fluctuations, across the brain, on closed-loop brain/body/environment interactions strongly supporting the idea that brain function cannot be fully understood through open-loop approaches alone

Incorporation of DPP6a and DPP6K Variants in Ternary Kv4 Channel Complex Reconstitutes Properties of A-type K Current in Rat Cerebellar Granule Cells

Dipeptidyl peptidase-like protein 6 (DPP6) proteins co-assemble with Kv4 channel α-subunits and Kv channel-interacting proteins (KChIPs) to form channel protein complexes underlying neuronal somatodendritic A-type potassium current (ISA). DPP6 proteins are expressed as N-terminal variants (DPP6a, DPP6K, DPP6S, DPP6L) that result from alternative mRNA initiation and exhibit overlapping expression patterns. Here, we study the role DPP6 variants play in shaping the functional properties of ISA found in cerebellar granule (CG) cells using quantitative RT-PCR and voltage-clamp recordings of whole-cell currents from reconstituted channel complexes and native ISA channels. Differential expression of DPP6 variants was detected in rat CG cells, with DPP6K (41±3%)>DPP6a (33±3%)>>DPP6S (18±2%)>DPP6L (8±3%). To better understand how DPP6 variants shape native neuronal ISA, we focused on studying interactions between the two dominant variants, DPP6K and DPP6a. Although previous studies did not identify unique functional effects of DPP6K, we find that the unique N-terminus of DPP6K modulates the effects of KChIP proteins, slowing recovery and producing a negative shift in the steady-state inactivation curve. By contrast, DPP6a uses its distinct N-terminus to directly confer rapid N-type inactivation independently of KChIP3a. When DPP6a and DPP6K are co-expressed in ratios similar to those found in CG cells, their distinct effects compete in modulating channel function. The more rapid inactivation from DPP6a dominates during strong depolarization; however, DPP6K produces a negative shift in the steady-state inactivation curve and introduces a slow phase of recovery from inactivation. A direct comparison to the native CG cell ISA shows that these mixed effects are present in the native channels. Our results support the hypothesis that the precise expression and co-assembly of different auxiliary subunit variants are important factors in shaping the ISA functional properties in specific neuronal populations

Towards neuro-inspired symbolic models of cognition: linking neural dynamics to behaviors through asynchronous communications

A computational architecture modeling the relation between perception and action is proposed. Basic brain processes representing synaptic plasticity are first abstracted through asynchronous communication protocols and implemented as virtual microcircuits. These are used in turn to build mesoscale circuits embodying parallel cognitive processes. Encoding these circuits into symbolic expressions gives finally rise to neuro-inspired programs that are compiled into pseudo-code to be interpreted by a virtual machine. Quantitative evaluation measures are given by the modification of synapse weights over time. This approach is illustrated by models of simple forms of behaviors exhibiting cognition up to the third level of animal awareness. As a potential benefit, symbolic models of emergent psychological mechanisms could lead to the discovery of the learning processes involved in the development of cognition. The executable specifications of an experimental platform allowing for the reproduction of simulated experiments are given in “Appendix”

Radix Sort For Vector Multiprocessors

We have designed a radix sort algorithm for vector multiprocessors and have implemented the algorithm on the CRAY Y-MP. On one processor of the Y-MP, our sort is over 5 times faster on large sorting problems than the optimized library sort provided by CRAY Research. On eight processors we achieve an additional speedup of almost 5, yielding a routine over 25 times faster than the library sort. Using this multiprocessor version, we can sort at a rate of 15 million 64-bit keys per second. Our sorting algorithm is adapted from a data-parallel algorithm previously designed for a highly parallel Single Instruction Multiple Data (SIMD) computer, the Connection Machine CM-2. To develop our version we introduce three general techniques for mapping data-parallel algorithms ontovector multiprocessors. These techniques allow us to fully vectorize and parallelize the algorithm. The paper also derives equations that model the performance of our algorithm on the Y-MP. These equations are then used t..

Scan Primitives for Vector Computers

The authors describe an optimized implementation of a set of scan (also called all-prefix-sums) primitives on a single processor of a CRAY Y-MP, and demonstrate that their use leads to greatly improved performance for several applications that cannot be vectorized with existing computer technology. The algorithm used to implement the scans is based on an algorithm for parallel computers. A set of segmented versions of these scans is only marginally more expensive than the unsegmented versions. The authors describe a radix sorting routine based on the scans that is 13 times faster than a Fortran version and within 20% of a highly optimized library sort routine, three operations on trees that are between 10 to 20 times faster than the corresponding C versions, and a connectionist learning algorithm that is 10 times faster than the corresponding C version for sparse and irregular network