Bi-Modal DRAM Cache: Improving Hit Rate, Hit Latency and Bandwidth

In this paper, we present Bi-Modal Cache - a flexible stacked DRAM cache organization which simultaneously achieves several objectives: (i) improved cache hit ratio, (ii) moving the tag storage overhead to DRAM, (iii) lower cache hit latency than tags-in-SRAM, and (iv) reduction in off-chip bandwidth wastage. The Bi-Modal Cache addresses the miss rate versus off-chip bandwidth dilemma by organizing the data in a bi-modal fashion - blocks with high spatial locality are organized as large blocks and those with little spatial locality as small blocks. By adaptively selecting the right granularity of storage for individual blocks at run-time, the proposed DRAM cache organization is able to make judicious use of the available DRAM cache capacity as well as reduce the off-chip memory bandwidth consumption. The Bi-Modal Cache improves cache hit latency despite moving the metadata to DRAM by means of a small SRAM based Way Locator. Further by leveraging the tremendous internal bandwidth and capacity that stacked DRAM organizations provide, the Bi-Modal Cache enables efficient concurrent accesses to tags and data to reduce hit time. Through detailed simulations, we demonstrate that the Bi-Modal Cache achieves overall performance improvement (in terms of Average Normalized Turnaround Time (ANTT)) of 10.8%, 13.8% and 14.0% in 4-core, 8-core and 16-core workloads respectively.

Field Reduction Electrodes for the Possible Improvement in the Pollution Flashover Performance of Porcelain Insulators

In this paper an attempt is made to study accurately, the field distribution for various types of porcelain/ceramic insulators used forhigh voltage transmission. The surface charge Simulation method is employed for the field computation. Novel field reduction electrodes are developed to reduce the maximum field around the pin region. In order to experimentally scrutinize the performance of discs with field reduction electrodes, special artificial pollution test facility was built and utilized. The experimental results show better improvement in the pollution flashover performance of string insulators.

Improvement in solar air collector performance with vaned diffuser

Modifications made in a solar air collector inlet duct to achieve uniform velocity of air in the absorber duct are described. Measurements of temperature and pressure at various points in the duct gave information on the distribution of air in the absorber duct. A thermal performance test conducted on the collector with a vaned diffuser showed some significant improvement compared with a diffuser without vanes.

Focused Prefetching: Performance Oriented Prefetching Based On Commit Stalls

Loads that miss in L1 or L2 caches and waiting for their data at the head of the ROB cause significant slow down in the form of commit stalls. We identify that most of these commit stalls are caused by a small set of loads, referred to as LIMCOS (Loads Incurring Majority of COmmit Stalls). We propose simple history-based classifiers that track commit stalls suffered by loads to help us identify this small set of loads. We study an application of these classifiers to prefetching. The classifiers are used to train the prefetcher to focus on the misses suffered by LIMCOS. This, referred to as focused prefetching, results in a 9.8% gain in IPC over naive GHB based delta correlation prefetcher along with a 20.3% reduction in memory traffic for a set of 17 memory-intensive SPEC2000 benchmarks. Another important impact of focused prefetching is a 61% improvement in the accuracy of prefetches. We demonstrate that the proposed classification criterion performs better than other existing criteria like criticality and delinquent loads. Also we show that the criterion of focusing on commit stalls is robust enough across cache levels and can be applied to any prefetcher without any modifications to the prefetcher.

Improvement in Intrusion Detection With Advances in Sensor Fusion

Various intrusion detection systems (IDSs) reported in the literature have shown distinct preferences for detecting a certain class of attack with improved accuracy, while performing moderately on the other classes. In view of the enormous computing power available in the present-day processors, deploying multiple IDSs in the same network to obtain best-of-breed solutions has been attempted earlier. The paper presented here addresses the problem of optimizing the performance of IDSs using sensor fusion with multiple sensors. The trade-off between the detection rate and false alarms with multiple sensors is highlighted. It is illustrated that the performance of the detector is better when the fusion threshold is determined according to the Chebyshev inequality. In the proposed data-dependent decision ( DD) fusion method, the performance optimization of ndividual IDSs is first addressed. A neural network supervised learner has been designed to determine the weights of individual IDSs depending on their reliability in detecting a certain attack. The final stage of this DD fusion architecture is a sensor fusion unit which does the weighted aggregation in order to make an appropriate decision. This paper theoretically models the fusion of IDSs for the purpose of demonstrating the improvement in performance, supplemented with the empirical evaluation.

High performance VLSI architecture design for H.264 CAVLC decoder

H.264 video standard achieves high quality video along with high data compression when compared to other existing video standards. H.264 uses context-based adaptive variable length coding (CAVLC) to code residual data in Baseline profile. In this paper we describe a novel architecture for CAVLC decoder including coeff-token decoder, level decoder total-zeros decoder and run-before decoder UMC library in 0.13 mu CMOS technology is used to synthesize the proposed design. The proposed design reduces chip area and improves critical path performance of CAVLC decoder in comparison with [1]. Macroblock level (including luma and chroma) pipeline processing for CAVLC is implemented with an average of 141 cycles (including pipeline buffering) per macroblock at 250MHz clock frequency. To compare our results with [1] clock frequency is constrained to 125MHz. The area required for the proposed architecture is 17586 gates, which is 22.1% improvement in comparison to [1]. We obtain a throughput of 1.73 * 10(6) macroblocks/second, which is 28% higher than that reported in [1]. The proposed design meets the processing requirement of 1080HD [5] video at 30frames/seconds.

Performance prediction and loss analysis of low specific speed submersible pumps

A performance prediction procedure is presented for low specific speed submersible pumps with a review of loss models given in the literature. Most of the loss theories discussed in this paper are one dimensional and improvements are made with good empiricism for the prediction to cover the entire range of operation of the low specific speed pumps. Loss correlations, particularly in the low flow range, are discussed. Prediction of the shape of efficiency-capacity and total head-capacity curves agrees well with the experimental results in almost the full range of operating conditions. The approach adopted in the present analysis, of estimating the losses in the individual components of a pump, provides means for improving the performance and identifying the problem areas in existing designs of the pumps. The investigation also provides a basis for selection of parameters for the optimal design of the pumps in which the maximum efficiency is an important design parameter. The scope for improvement in the prediction procedure with the nature of flow phenomena in the low flow region has been discussed in detail.

Study of Pulsed Plasma in a Crossed Flow Dielectric Barrier Discharge Reactor for Improvement of NOx Removal in Raw Diesel Engine Exhaust

Improved performance of plasma in raw engine exhaust treatment is reported. A new type of reactor referred to as of cross-flow dielectric barrier discharge (DBD) was used, in which the gas flow is perpendicular to the corona electrode. In raw exhaust environment, the cross-flow (radial-flow) reactor exhibits a superior performance with regard to NOX removal when compared to that with axial flow of gas. Experiments were conducted at different flow rates ranging from 2 L/min to 25 L/min. The plasma assisted barrier discharge reactor has shown encouraging results in NOx removal at high flow rates.

Evaluation and improvement of total transfer capability - A case study

With deregulation, the total transfer capability (TTC) calculation, which is the basis for evaluating available transfer capability (ATC), has become very significant. TTC is an important index in power markets with large volume of inter-area power exchanges and wheeling transactions taking place on an hourly basis. Its computation helps to achieve a viable technical and commercial transmission operation. The aim of the paper is to evaluate TTC in the interconnections and also to improve it using reactive optimization technique and UPFC devices. Computations are carried out for normal and contingency cases such as single line, tie line and generator outages. Base and optimized results are presented, and the results show how reactive optimization and unified power flow controller help to improve the system conditions. In this paper repeated power flow method is used to calculate TTC due to its ease of implementation. A case study is carried out on a 205 bus equivalent system, a part of Indian Southern grid. Parameters like voltage magnitude, L-index, minimum singular value and MW losses are computed to analyze the system performance.

Evaluation of bearing capacity improvement using composite grids

Recently, composite reinforcements in which combinations of materials and material forms such as strips, grids, and strips and anchors, depending on requirements have proven to be effective in various ground improvement applications. Composite geogrids studied in this paper belong to the category of composite reinforcements and are useful for bearing capacity improvement. The paper presents evaluation of results of bearing capacity tests conducted oil a composite geogrid, made of composite reinforcement consisting of steel and cement mortar. The study shows that the behavior of composite reinforcements follows the general trends observed in the case of conventional geogrids, with reference to the depth of first layer below the footing, number of layers of reinforcement, and vertical spacing of the reinforcement. Results show that the performance is comparable to that of a conventional polymer geogrid.

Improvement of protein structure comparison using a structural alphabet

The three dimensional structure of a protein provides major insights into its function. Protein structure comparison has implications in functional and evolutionary studies. A structural alphabet (SA) is a library of local protein structure prototypes that can abstract every part of protein main chain conformation. Protein Blocks (PBS) is a widely used SA, composed of 16 prototypes, each representing a pentapeptide backbone conformation defined in terms of dihedral angles. Through this description, the 3D structural information can be translated into a 1D sequence of PBs. In a previous study, we have used this approach to compare protein structures encoded in terms of PBs. A classical sequence alignment procedure based on dynamic programming was used, with a dedicated PB Substitution Matrix (SM). PB-based pairwise structural alignment method gave an excellent performance, when compared to other established methods for mining. In this study, we have (i) refined the SMs and (ii) improved the Protein Block Alignment methodology (named as iPBA). The SM was normalized in regards to sequence and structural similarity. Alignment of protein structures often involves similar structural regions separated by dissimilar stretches. A dynamic programming algorithm that weighs these local similar stretches has been designed. Amino acid substitutions scores were also coupled linearly with the PB substitutions. iPBA improves (i) the mining efficiency rate by 6.8% and (ii) more than 82% of the alignments have a better quality. A higher efficiency in aligning multi-domain proteins could be also demonstrated. The quality of alignment is better than DALI and MUSTANG in 81.3% of the cases. Thus our study has resulted in an impressive improvement in the quality of protein structural alignment. (C) 2011 Elsevier Masson SAS. All rights reserved.

Performance Enhancement of the Tunnel Field Effect Transistor using SiGe Source

Due to extremely low off state current (IOFF) and excellent sub-threshold characteristics, the tunnel field effect transistor (TFET) has attracted a lot of attention for low standby power applications. In this work, we aim to increase the on state current (ION) of the device. A novel device architecture with a SiGe source is proposed. The proposed structure shows an order of improvement in ION compared to the conventional Si structure. A process flow adaptable to conventional CMOS technology is also addressed.

A Simulation Based Study and Analysis of Double Gate Tunnel FET Performance for Low Stand-By Power Applications

The conventional metal oxide semiconductor field effect transistor (MOSFET)may not be suitable for future low standby power (LSTP) applications due to its high off-state current as the sub-threshold swing is theoretically limited to 60mV/decade. Tunnel field effect transistor (TFET) based on gate controlled band to band tunneling has attracted attention for such applications due to its extremely small sub-threshold swing (much less than 60mV/decade). This paper takes a simulation approach to gain some insight into its electrostatics and the carrier transport mechanism. Using 2D device simulations, a thorough study and analysis of the electrical parameters of the planar double gate TFET is performed. Due to excellent sub-threshold characteristics and a reverse biased structure, it offers orders of magnitude less leakage current compared to the conventional MOSFET. In this work, it is shown that the device can be scaled down to channel lengths as small as 30 nm without affecting its performance. Also, it is observed that the bulk region of the device plays a major role in determining the sub-threshold characteristics of the device and considerable improvement in performance (in terms of ION/IOFF ratio) can be achieved if the thickness of the device is reduced. An ION/IOFF ratio of 2x1012 and a minimum point sub-threshold swing of 22mV/decade is obtained.

Model-following Neuro-adaptive approach for robust control of high performance aircrafts

Based on dynamic inversion, a relatively straightforward approach is presented in this paper for nonlinear flight control design of high performance aircrafts, which does not require the normal and lateral acceleration commands to be first transferred to body rates before computing the required control inputs. This leads to substantial improvement of the tracking response. Promising results are obtained from six degree-offreedom simulation studies of F-16 aircraft, which are found to be superior as compared to an existing approach (which is also based on dynamic inversion). The new approach has two potential benefits, namely reduced oscillatory response (including elimination of non-minimum phase behavior) and reduced control magnitude. Next, a model-following neuron-adaptive design is augmented the nominal design in order to assure robust performance in the presence of parameter inaccuracies in the model. Note that in the approach the model update takes place adaptively online and hence it is philosophically similar to indirect adaptive control. However, unlike a typical indirect adaptive control approach, there is no need to update the individual parameters explicitly. Instead the inaccuracy in the system output dynamics is captured directly and then used in modifying the control. This leads to faster adaptation, which helps in stabilizing the unstable plant quicker. The robustness study from a large number of simulations shows that the adaptive design has good amount of robustness with respect to the expected parameter inaccuracies in the model.

Performance analysis of UDP with energy efficient link layer on Markov fading channels

In this paper, we analyze the throughput and energy efficiency performance of user datagram protocol (UDP) using linear, binary exponential, and geometric backoff algorithms at the link layer (LL) on point-to-point wireless fading links. Using a first-order Markov chain representation of the packet success/failure process on fading channels, we derive analytical expressions for throughput and energy efficiency of UDP/LL with and without LL backoff. The analytical results are verified through simulations. We also evaluate the mean delay and delay variation of voice packets and energy efficiency performance over a wireless link that uses UDP for transport of voice packets and the proposed backoff algorithms at the LL. We show that the proposed LL backoff algorithms achieve energy efficiency improvement of the order of 2-3 dB compared to LL with no backoff, without compromising much on the throughput and delay performance at the UDP layer. Such energy savings through protocol means will improve the battery life in wireless mobile terminals.