Architecture-aware configuration and scheduling of matrix multiplication on asymmetric multicore processors

Asymmetric multicore processors have recently emerged as an appealing technology for severely energy-constrained environments, especially in mobile appliances where heterogeneity in applications is mainstream. In addition, given the growing interest for low-power high performance computing, this type of architectures is also being investigated as a means to improve the throughput-per-Watt of complex scientific applications on clusters of commodity systems-on-chip. In this paper, we design and embed several architecture-aware optimizations into a multi-threaded general matrix multiplication (gemm), a key operation of the BLAS, in order to obtain a high performance implementation for ARM big.LITTLE AMPs. Our solution is based on the reference implementation of gemm in the BLIS library, and integrates a cache-aware configuration as well as asymmetric-static and dynamic scheduling strategies that carefully tune and distribute the operation’s micro-kernels among the big and LITTLE cores of the target processor. The experimental results on a Samsung Exynos 5422, a system-on-chip with ARM Cortex-A15 and Cortex-A7 clusters that implements the big.LITTLE model, expose that our cache-aware versions of gemm with asymmetric scheduling attain important gains in performance with respect to its architecture-oblivious counterparts while exploiting all the resources of the AMP to deliver considerable energy efficiency.     

Proprioceptors and their contribution to somatosensory mapping: complex messages require complex processing

This review of other people's work concentrates on two matters. First, which of the various receptors are chiefly involved in creating the central representations or maps of the body that both underlie the conscious perception of our body image and are needed to control our motor performance. Second, how are these relatively well-charted signals used in sensorimotor mapping, with particular attention paid to various human psychophysical observations and illusions that throw light on the central integrative mechanisms involved. Detailed citation is largely restricted to developments since earlier reviews.     

A task scheduling algorithm for arbitrarily-connected processors with awareness of link contention

In this paper, we present a new task scheduling algorithm, called Contention-Aware Scheduling (CAS) algorithm, with the objective of delivering good quality of schedules in low running-time by considering contention on links of arbitrarily-connected, heterogeneous processors. The CAS algorithm schedules tasks on processors and messages on links by considering the earliest finish time attribute with the virtual cut-through (VCT) or the store-and-forward (SAF) switching. There are three types of CAS algorithm presented in this paper, which differ in ordering the messages from immediate predecessor tasks. As part of the experimental study, the performance of the CAS algorithm is compared with two well-known APN (arbitrary processor network) scheduling algorithms. Experiments on the results of the synthetic benchmarks and the task graphs of the well-known problems clearly show that our CAS algorithm outperforms the related work with respect to performance (given in normalized schedule length) and cost (given in running time) to generate output schedules. Ali Fuat Alkaya received the B.Sc. degree in mathematics from Koc University, Istanbul, Turkey in 1998, and the M.Sc. degree in computer engineering from Marmara University, Istanbul, Turkey in 2002. He is currently a Ph.D. student in engineering management department at the same university. His research interests include task scheduling and analysis of algorithms. Haluk Rahmi Topcuoglu received the B.Sc. and M.Sc. degrees in computer engineering from Bogazici University, Istanbul, Turkey, in 1991 and 1993, respectively. He received the Ph.D. degree in computer science from Syracuse University in 1999. He has been on the faculty at Marmara University, Istanbul, Turkey since Fall 1999, where he is currently an Associate Professor in computer engineering department. His main research interests are task scheduling and mapping in parallel and distributed systems; parallel processing; evolutionary algorithms and their applicability for stationary and dynamic environments. He is a member of the ACM, the IEEE, and the IEEE Computer Society. e-mail: haluk@eng.marmara.edu.tr e-mail: falkaya@eng.marmara.edu.tr     

Energy aware scheduling of deadline-constrained tasks in cloud computing

Energy efficiency is the predominant issue which troubles the modern ICT industry. The ever-increasing ICT innovations and services have exponentially added to the energy demands and this proliferated the urgency of fostering the awareness for development of energy efficiency mechanisms. But for a successful and effective accomplishment of such mechanisms, the support of underlying ICT platform is significant. Eventually, Cloud computing has gained attention and has emerged as a panacea to beat the energy consumption issues. This paper scrutinizes the importance of multicore processors, virtualization and consolidation techniques for achieving energy efficiency in Cloud computing. It proposes Green Cloud Scheduling Model (GCSM) that exploits the heterogeneity of tasks and resources with the help of a scheduler unit which allocates and schedules deadline-constrained tasks delimited to only energy conscious nodes. GCSM makes energy-aware task allocation decisions dynamically and aims to prevent performance degradation and achieves desired QoS. The evaluation and comparative analysis of the proposed model with two other techniques is done by setting up a Cloud environment. The results indicate that GCSM achieves 71 % of energy savings and high performance in terms of deadline fulfillment.     

Peptide mapping of heterogeneous protein samples.

A simple two-dimensional electrophoretic method for peptide mapping of heterogeneous protein samples is presented. The reduced and denatured proteins of the mixture are separated in a first dimension by sodium dodecyl sulfate-polyacrylamide slab gel electrophoresis. After completion of the electrophoresis, the whole gel lane is equilibrated in stacking gel buffer and is transferred at right angles onto a second slab gel. A protease solution is overlayed on the gel lane and a partial proteolysis of the proteins to be analyzed is performed during the stacking phase of the second electrophoresis. The second electrophoresis resolves the characteristic pattern of peptides of each individual protein as a series of spots located below the original position of the undigested protein. The peptide maps of the following samples are presented as examples: protein P23 and P23* of bacteriophage T4, membranes of Dictyostelium discoideum, membranes of human erythrocytes, and 35S-labeled proteins of D. discoideum synthesized in vivo or in a cell-free wheat germ extract. In complex samples, up to 20 individual proteins can be analyzed at once and a protein comprising only 1% of the total sample generates a clearly identifiable peptide pattern. Good reproducibility of the patterns obtained allows the comparison of samples of different origins.     

Model of interactions in biology and application to heterogeneous network in yeast

A major challenge for bioinformatics and theoretical biology is to build and analyse a unified model of biological knowledge resulting from high-throughput experiment data. Former work analyzed heterogeneous data (protein-protein interactions, genetic regulation, metabolism, synexpression) by modelling them by graphs. These models are unable to represent the qualitative dynamics of the reactions or to model the n-ary interactions. Here, MIB, the Model of Interactions in Biology, a bipartite model of biological networks, is introduced, and its use for topological analysis of the heterogeneous network is presented. Heterogeneous loops and links between synexpression pattern and underlying molecular mechanisms are proposed.     

Purposive behavior and cognitive mapping: a neural network model

This study presents a real-time, biologically plausible neural network approach to purposive behavior and cognitive mapping. The system is composed of (a) an action system, consisting of a goal-seeking neural mechanism controlled by a motivational system; and (b) a cognitive system, involving a neural cognitive map. The goal-seeking mechanism displays exploratory behavior until either (a) the goal is found or (b) an adequate prediction of the goal is generated. The cognitive map built by the network is a top logical map, i.e., it represents only the adjacency, but not distances or directions, between places. The network has recurrent and non-recurrent properties that allow the reading of the cognitive map without modifying it. Two types of predictions are introduced: fast-time and real-time predictions. Fast-time predictions are produced in advance of what occurs in real time, when the information stored in the cognitive map is used to predict the remote future. Real-time predictions are generated simultaneously with the occurrence of environmental events, when the information stored in the cognitive map is being updated. Computer simulations show that the network successfully describes latent learning and detour behavior in rats. In addition, simulations demonstrate that the network can be applied to problem-solving paradigms such as the Tower of Hanoi puzzle.     

The effective size of a metapopulation living in a heterogeneous patch network

I analyze stochastic patch occupancy models (SPOMs), which record habitat patches as empty or occupied. A problem with SPOMs has been that if the spatial structure of a heterogeneous habitat patch network is taken into account, the computational effort needed to analyze a SPOM grows as a power of 2n, where n is the number of habitat patches. I propose a computationally feasible approximation method, which approximates the behavior of a heterogeneous SPOM by an "ideal" metapopulation inhabiting a network of identical and equally connected habitat patches. The transformation to the ideal metapopulation is based on weighting the individual patch occupancies by the dynamic values of the habitat patches, which may be calculated from the deterministic mean-field approximation of the original SPOM. Conceptually, the method resembles the calculation of the effective size of a population in the context of population genetics. I demonstrate how the method may be applied to SPOMs with flexible structural assumptions and with spatially correlated and temporally varying parameter values. I apply the method to a real habitat patch network inhabited by the Glanville fritillary butterfly, illustrating that the metapopulation dynamics of this species are essentially driven by temporal variability in the environmental conditions.     

An effective reliability-driven technique of allocating tasks on heterogeneous cluster systems

In large-scale heterogeneous cluster computing systems, processor and network failures are inevitable and can have an adverse effect on applications executing on such systems. One way of taking failures into account is to employ a reliable scheduling algorithm. However, most existing scheduling algorithms for precedence constrained tasks in heterogeneous systems only consider scheduling length, and not efficiently satisfy the reliability requirements of task. In recognition of this problem, we build an application reliability analysis model based on Weibull distribution, which can dynamically measure the reliability of task executing on heterogeneous cluster with arbitrary networks architectures. Then, we propose a reliability-driven earliest finish time with duplication scheduling algorithm (REFTD) which incorporates task reliability overhead into scheduling. Furthermore, to improve system reliability, it duplicates task as if task hazard rate is more than threshold \(\theta \) . The comparison study, based on both randomly generated graphs and the graphs of some real applications, shows that our scheduling algorithm can shorten schedule length and improve system reliability significantly.     

Linking movement and reproductive history of brook trout to assess habitat connectivity in a heterogeneous stream network

相似文献   

Epileptic seizures in a heterogeneous excitatory network with short-term plasticity

Epilepsy involves a diverse group of abnormalities, including molecular and cellular disorders. These abnormalities prove to be associated with the changes in local excitability and synaptic dynamics. Correspondingly, the epileptic processes including onset, propagation and generalized seizure may be related with the alterations of excitability and synapse. In this paper, three regions, epileptogenic zone (EZ), propagation area and normal region, were defined and represented by neuronal population model with heterogeneous excitability, respectively. In order to describe the synaptic behavior that the strength was enhanced and maintained at a high level for a short term under a high frequency spike train, a novel activity-dependent short-term plasticity model was proposed. Bifurcation analysis showed that the presence of hyperexcitability could increase the seizure susceptibility of local area, leading to epileptic discharges first seen in the EZ. Meanwhile, recurrent epileptic activities might result in the transition of synaptic strength from weak state to high level, augmenting synaptic depolarizations in non-epileptic neurons as the experimental findings. Numerical simulation based on a full-connected weighted network could qualitatively demonstrate the epileptic process that the propagation area and normal region were successively recruited by the EZ. Furthermore, cross recurrence plot was used to explore the synchronization between neuronal populations, and the global synchronization index was introduced to measure the global synchronization. Results suggested that the synchronization between the EZ and other region was significantly enhanced with the occurrence of seizure. Interestingly, the desynchronization phenomenon was also observed during seizure initiation and propagation as reported before. Therefore, heterogeneous excitability and short-term plasticity are believed to play an important role in the epileptic process. This study may provide novel insights into the mechanism of epileptogenesis.     

A comparison of utility-oriented algorithms for scheduling parallel tasks in multi-cluster grid

Scheduling parallel tasks in multi-cluster grid can be seen as two interdependent problems: cluster allocation and scheduling parallel task on the allocated cluster. In this paper both rigid and moldable parallel tasks are considered. We propose a theoretical model of utility-oriented parallel task scheduling in multi-cluster grid with advance reservations. On the basis of the model we present an approximation algorithm, a repair strategy based genetic algorithm and greedy heuristics MaxMax, T-Sufferage and R-Sufferage to solve the two interdependent problems. We compare the performance of these algorithms in aspect of utility optimality and timing results. Simulation results show on average the (1+α)-approximation algorithm achieves the best trade-off between utility optimality and timing. Genetic algorithm could achieve better utility than greedy heuristics and approximate algorithm at expensive time cost. Greedy heuristics do not perform equally well when adapted to different utility functions while the approximation algorithm shows its intrinsic stable performance.     

Isolation of a nuclear ribonucleoprotein network that contains heterogeneous RNA and is bound to the nuclear envelope.

Rapidly labeled polydispersed nuclear RNA is part of a ribonucleoprotein (RNP) network which in turn is tightly bound to the nuclear membrane. The membranous attachment, therefore, established a connection between chromatin and cytoplasm. The ultrastructure of the RNP network comprises fibrils and granules similar to those observed in intact nuclei. When bound to the nuclear membrane it has the composition of 63% protein, 14% RNA, 0.4% DNA, and 22.6% lipids. The proportion of lipids diminishes to 2.2% when nuclear membrane is not present. Chromatin, nucleoli, and ribosomes are minor contaminants since histones and ribosomal proteins are not detectable in polyacrylamide gel electrophoresis. Nuclear disruption at high pressure in a French pressure cell causes fragmentation of the RNP network into a series of polydispersed RNP particles. Fragmentation can be prevented by using mild pressure, or by disrupting nuclei with high salt buffer and digesting the dispersed chromatin with deoxyribonuclease. A RNP network, almost free of membrane, is also obtained if the nucleus is deprived of its envelope by treatment with Triton X-100. Since no polydispersed RNP particles are found following dissolution of the nuclear membrane, it is assumed that the particles are components of the RNP network whose fragmentation occurs as a consequence of two processes: (a) activation of nuclear nucleases and (b) shearing forces.     

Fundamentals of protein interaction network mapping

Studying protein interaction networks of all proteins in an organism (“interactomes”) remains one of the major challenges in modern biomedicine. Such information is crucial to understanding cellular pathways and developing effective therapies for the treatment of human diseases. Over the past two decades, diverse biochemical, genetic, and cell biological methods have been developed to map interactomes. In this review, we highlight basic principles of interactome mapping. Specifically, we discuss the strengths and weaknesses of individual assays, how to select a method appropriate for the problem being studied, and provide general guidelines for carrying out the necessary follow‐up analyses. In addition, we discuss computational methods to predict, map, and visualize interactomes, and provide a summary of some of the most important interactome resources. We hope that this review serves as both a useful overview of the field and a guide to help more scientists actively employ these powerful approaches in their research.