16272826
Analyzing the impact of on-chip network traffic on program phases for CMPs
It is known that the execution of programs exhibits repetitive phases; in other words, the execution of programs can be partitioned into segments of execution, during which the application exhibits unique architectural properties. This property has been used for various optimization goals. In addition, phase information is utilized to reduce the run time of the architectural simulation. Conventionally, an application is examined in an architecture-independent manner (such as the number of times a basic block is executed) to extract information about the phases and then only the representative execution intervals are executed to analyze architectural choices. We claim that such approaches are becoming inadequate in the many-core era as application execution is not dominated by the instructions only, but instead the communication structure of the application is becoming as important as the instruction behavior. Hence, we propose to utilize communication behavior to determine the phases of an application. Our results reveal that the inclusion of the communication information can increase the accuracy of the phase detection significantly. Specifically, for SPLASH2 and MineBench applications, the average (geometric mean) CPI error rate with the instruction-based phase detection is 11.01%, while our phase detection scheme has an average error rate of 3.41% when compared to the simulations that run the applications to completion.
6412815
Automated task distribution in multicore network processors using statistical analysis
Chip multiprocessor designs are the most common types of architectures seen in Network Processors. As the Network Processors are used to implement increasingly complicated applications, task distribution among the cores is becoming an important problem. In this paper, we propose a new task allocation scheme for such architectures. This scheme relies on the inherent modular nature of the networking applications and intelligently distributes modules among different execution cores. Additionally, we selectively replicate modules to parallelize execution of tasks having longer processing time. We have developed a technique that uses the probability distribution of the execution times of different modules in the networking applications. The proposed schemes result in resource utilization of up to 95%, 89%, and 84% on average for the processors with 2, 4, and 8 cores, respectively. The schemes are highly scalable and can improve the throughput by 6.72 times for 8 core processors, aggregated over four representative applications. The combination of selective replication of modules and variation-aware task allocation result in up to 12.5% (9.9% on average) performance improvement as compared to a scheme based on just mean processing time.
10896727
Firefly: illuminating future network-on-chip with nanophotonics
Future many-core processors will require high-performance yet energy-efficient on-chip networks to provide a communication substrate for the increasing number of cores. Recent advances in silicon nanophotonics create new opportunities for on-chip networks. To efficiently exploit the benefits of nanophotonics, we propose Firefly - a hybrid, hierarchical network architecture. Firefly consists of clusters of nodes that are connected using conventional, electrical signaling while the inter-cluster communication is done using nanophotonics - exploiting the benefits of electrical signaling for short, local communication while nanophotonics is used only for global communication to realize an efficient on-chip network. Crossbar architecture is used for inter-cluster communication. However, to avoid global arbitration, the crossbar is partitioned into multiple, logical crossbars and their arbitration is localized. Our evaluations show that Firefly improves the performance by up to 57% compared to an all-electrical concentrated mesh (CMESH) topology on adversarial traffic patterns and up to 54% compared to an all-optical crossbar (OP XBAR) on traffic patterns with locality. If the energy-delay-product is compared, Firefly improves the efficiency of the on-chip network by up to 51% and 38% compared to CMESH and OP XBAR, respectively.
11247110
Sustaining Incentive in Grid Resource Allocation: A Reinforcement Learning Approach
Encouraging resource sharing and cooperation among different parties is one of the central goals of grid computing. In real environments, however, selfish or malicious nodes can seriously degrade the sharing and cooperation performance of a grid. To solve this problem, we propose QIA, a novel Q-learning based resource Allocation mechanism that sustains Incentive for every participating node. Exploiting an economic model, QIA recognizes the importance of trust factor when allocating resources. Each provider considers a combined metric, which is composed of the bid price and the trust value, of a requester when allocating its resources. The incomplete information is a key issue for a provider in determining the relative weight of bid price and trust value. We propose a reinforcement Q- learning technique to resolve the issue, which is able to adapt the dynamics of grid environments. We implemented QIA in a real grid test-bed, CROWN grid. Comprehensive experiments have been conducted, which demonstrate the efficacy of QIA.
7672026
A power and temperature aware DRAM architecture
Technological advances enable modern processors to utilize increasingly larger DRAMs with rising access frequencies. This is leading to high power consumption and operating temperature in DRAM chips. As a result, temperature management has become a real and pressing issue in high performance DRAM systems. Traditional low power techniques are not suitable for high performance DRAM systems with high bandwidth. In this paper, we propose and evaluate a customized DRAM low power technique based on page hit aware write buffer (PHA-WB). Our proposed approach reduces DRAM system power consumption and temperature without any performance penalty. Our experiments show that a system with a 64-entry PHA-WB could reduce the total DRAM power consumption by up to 22.0% (9.6% on average). The peak and average temperature reductions are 6.1degC and 2.1degC, respectively.
7761771
Access control in peer-to-peer collaborative systems
As an emerging model of communication and computation, peer-to-peer networking represents a fully distributed, cooperative network design, and has recently gained significant acceptance. Peer groups share the properties of peer-to-peer overlay network, including full decentralization, symmetric abilities, and dynamism, which make security problems more complicated. In this paper, we propose a fine-grained and attribute-based access control framework for peer-to-peer systems. This design employs a novel policy model, which extends role-based trust management language RT to satisfy security requirements of peer groups. Intend for a pure decentralized model without centralized server, our framework presents distributed delegation authorization mechanism, which could avoid single point of failure. We also introduce our implementation experience.
5191068
Predicting the activity phase of a follower neuron with A-current in an inhibitory network
The transient potassium A-current is present in most neurons and plays an important role in determining the timing of action potentials. We examine the role of the A-current in the activity phase of a follower neuron in a rhythmic feed-forward inhibitory network with a reduced three-variable model and conduct experiments to verify the usefulness of our model. Using geometric analysis of dynamical systems, we explore the factors that determine the onset of activity in a follower neuron following release from inhibition. We first analyze the behavior of the follower neuron in a single cycle and find that the phase plane structure of the model can be used to predict the potential behaviors of the follower neuron following release from inhibition. We show that, depending on the relative scales of the inactivation time constant of the A-current and the time constant of the recovery variable, the follower neuron may or may not reach its active state following inhibition. Our simple model is used to derive a recursive set of equations to predict the contribution of the A-current parameters in determining the activity phase of a follower neuron as a function of the duration and frequency of the inhibitory input it receives. These equations can be used to demonstrate the dependence of activity phase on the period and duty cycle of the periodic inhibition, as seen by comparing the predictions of the model with the activity of the pyloric constrictor (PY) neurons in the crustacean pyloric network.
2679883
Observation-based proactive communication in team cooperation
Observation and communication are important aspects of agent teamwork. We employ the agent's observability as the major means for individual agents to reason about the environment and other team members. We focus on how to represent agents' observability and how to include it into the basic reasoning for proactive communication. The syntax and the operational semantics of observability are given. Preliminary experiments are carried out to study the effectiveness of different aspects of observability.
9462041
HPtaa database-potential target genes for clinical diagnosis and immunotherapy of human carcinoma
Tumor-associated antigens (TAAs) have been the most actively employed targets in the clinical diagnosis and treatment of human carcinoma, such as PSA in the diagnosis of prostate cancer and NY-ESO-1 in the immunotherapy of melanoma and other cancers. However, identification of TAAs has often been hampered by the complicated and laborsome laboratory procedures. In order to accelerate the process of tumor antigen discovery, and thereby improve diagnosis and treatment of human carcinoma, we have made an effort to establish a publicly available Human Potential Tumor Associated Antigen database (HPtaa) with potential TAAs identified by in silico computing (http://www.hptaa.org). Tumor specificity was chosen as the core of tumor antigen evaluation, together with other relevant clues. Various platforms of gene expression, including microarray, expressed sequence tag and SAGE data, were processed and integrated by several penalty algorithms. A total of 3518 potential TAAs have been included in the database, which is freely available to academic users. As far as we know, this database is the first one addressing human potential TAAs, and the first one integrating various kinds of expression platforms for one purpose.
29942985
Poisson approximation for significance in genome-wide ChIP-chip tiling arrays
MOTIVATION
A genome-wide ChIP-chip tiling array study requires millions of simultaneous comparisons of hybridization for significance. Controlling the false positive rate in genome-wide tiling array studies is very important, because the number of computationally identified regions can easily go beyond the capability of experimental verification. No accurate and efficient method exists for evaluating statistical significance in tiling arrays. The Bonferroni method is overly conservative and the permutation test is time consuming for genome-wide studies.


RESULT
Motivated by the Poisson clumping heuristic, we propose an accurate and efficient method for evaluating statistical significance in genome-wide ChIP-chip tiling arrays. The method works accurately for any large number of multiple comparisons, and the computational cost for evaluating P-values does not increase with the total number of tests. Based on a moving window approach, we demonstrate how to combine results using various window sizes to increase the detection power while maintaining a specified type I error rate. We further introduce a new false discovery rate control that is more appropriate in measuring the false proportion of binding intervals in tiling array analysis. Our method is general and can be applied to many large-scale genomic and genetic studies.


AVAILABILITY
http://www.stat.psu.edu/~yuzhang/pass.tar
205397705
On the system of rational difference equations xn=A + 1/yn-p, yn=A+yn-1/xn-tyn-s
Abstract In this paper, we study the behavior of the positive solutions of the system of two difference equations x n = A + 1 y n - p , y n = A + y n - 1 x n - r y n - s , n = 1 , 2 , … , where p ⩾ 1, r ⩾ 1, s ⩾ 1, A ⩾ 0, and x1−r, x2−r, … , x0, y1−max{p,s}, y2−max{p,s}, … , y0 are positive real numbers.