Recent work in the FPGA acceleration of molecular dynamics simulation has shown that including on-the-fly neighbor list calculation (particle filtering) in the device has the potential for an 80× per core speed-u...
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Recent work in the FPGA acceleration of molecular dynamics simulation has shown that including on-the-fly neighbor list calculation (particle filtering) in the device has the potential for an 80× per core speed-up over the CPU-based reference code and so to make the approach competitive with other computing technologies. In this paper we report on progress and challenges in advancing this work towards the creation of a production system, especially one capable of running on a large-scale system such as the Novo-G. The current version consists of an FPGA-accelerated NAMD-lite running on a PC with a Gidel PROCStar III. The most important implementation issues include software integration, handling exclusion, and modifying the force pipeline. In the last of these we have added support for Particle-Mesh-Ewald and augmented the Lennard-Jones calculation with a switching function. In experiments, we find that energy stability so far appears to be acceptable, but that longer simulations are needed. Due primarily to the added complexity of the force pipelines, performance is somewhat diminished from the previous study; we find, however, that porting to a newer (existing) device will more than compensate for this loss.
This paper proposes a method which gives symbolic model of the interconnected linear system using the adjacency matrix which represent the system. When there exist any algebraic loops in the system, they are reduced t...
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Binding site mapping refers to the computational prediction of the regions on a protein surface that are likely to bind a small molecule with high affinity. The process involves flexibly docking a variety of small mol...
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ISBN:
(纸本)9781424465330
Binding site mapping refers to the computational prediction of the regions on a protein surface that are likely to bind a small molecule with high affinity. The process involves flexibly docking a variety of small molecule probes and finding a consensus site that binds most of those probes. Due to the computational complexity of flexible docking, the process is often split into two steps: the first performs rigid docking between the protein and the probe; the second models the side chain flexibility by energy-minimizing the (few thousand) top scoring protein-probe complexes generated by the first step. Both these steps are computationally very expensive, requiring many hours of runtime per probe on a serial CPU. In the current article, we accelerate a production mapping software program using NVIDIA GPUs. We accelerate both the rigid-docking and the energy minimization steps of the program. The result is a 30× speedup on rigid docking and 12× on energy minimization, resulting in a 13× overall speedup over the current single core implementation.
This paper presents a new analog ATPG (AATPG) framework that generates near-optimal test stimulus for the digitally-assisted adaptive equalizers in high-speed serial links. Based on the dynamic-signature-based testing...
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The Internet and related technologies have created an interconnected world in which we can exchange information easily, process tasks collaboratively, and form communities among users with similar interests. This allo...
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In this paper, an improved new design support system characterized by multigranularity is proposed. Previous studies has focused on only visualization of non-dominated solutions (NDSs), but our method aims to perform ...
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Search engines and information retrieval (IR) systems provide a mechanism for users to access large amounts of information available through the Internet. However, in order to find the desired information, the user ha...
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Search engines and information retrieval (IR) systems provide a mechanism for users to access large amounts of information available through the Internet. However, in order to find the desired information, the user has to go through a staggering amount of information retrieved from highly dynamic resources. Experimental results show that the approach proposed for constructing specialized domains improves the precision of information retrieval. Our approach involves enriching the user's query with related linguistic semantic and statistical semantic related concept terms. We employ natural language process (NLP) techniques such as WordNet engine to enrich the user's query with semantic lexical synonymous terms and a probabilistic topic model such as latent dirichet allocation (LDA) to extract highly ranked topic from a query's retrieved information. Furthermore, an intelligent learning algorithm, reinforcement learning (RL) is integrated into the design to assist end users in selecting the concept domains that are most relevant to their needs.
A bilateral control robot is one of the master-slave teleoperation robots. Consider two robots, a master robot is manipulated by human operators and a slave robot contacts remote environment. Decoupling of a force con...
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High-quality services must keep working reliably and efficiently, and service compositions are no exception. As they integrate several internal and external services over the network, they need to be carefully designe...
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High-quality services must keep working reliably and efficiently, and service compositions are no exception. As they integrate several internal and external services over the network, they need to be carefully designed to meet their performance requirements. Current approaches assist developers in estimating whether the selected services can fulfill those requirements. However, they do not help developers define requirements for services lacking performance constraints and historical data. Manually estimating these constraints is a time-consuming process which might underestimate or overestimate the required performance, incurring in additional costs. This work presents the first version of two algorithms which infer the missing performance constraints from a service composition model. The algorithms are designed to spread equally the load across the composition according to the probability and frequency each service is invoked, and to check the consistency of the performance constraints of each service with those of the composition.
We propose a new distributed alarm correlation and fault identification in computer networks. The managed network is divided into a disjoint management domains and each management domain is assigned a dedicated intell...
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ISBN:
(纸本)9781424457267;9780769539614
We propose a new distributed alarm correlation and fault identification in computer networks. The managed network is divided into a disjoint management domains and each management domain is assigned a dedicated intelligent agent. The intelligent agent is responsible for collecting, analyzing, and correlating alarms emitted form emitted from its constituent entities in its domain. In the framework of Dempster-Shafer evidence theory, each agent perceives each alarm as a piece of evidence in the occurrence of a certain fault hypothesis and correlates the received alarms into a single alarm called local composite alarm, which encapsulates the agent's partial view of the current status of the managed system. While the alarm correlation process is performed locally, each intelligent agent is able to correlate its alarms globally. These local composite alarms are, in turn, sent to a higher agent whose task is to fuse these alarms and form a global view of operation status of the running network. Extensive experimentations have demonstrated that the proposed approach is more alarm loss tolerant than the codebook based approaches and hence shown its effectiveness in a usually noisy network environment.
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