FPGA organization for the fast path-based neural branch predictor

This paper develops cycle-level FPGA circuits of an organization for a fast path-based neural branch predictor Our results suggest that practical sizes of prediction tables are limited to around 32 KB to 64 KB in current FPGA technology due mainly to FPGA area of logic resources to maintain the tables. However the predictor scales well in terms of prediction speed. Table sizes alone should not be used as the only metric for hardware budget when comparing neural-based predictor to predictors of totally different organizations. This paper also gives early evidence to shift the attention on to the recovery from mis-prediction latency rather than on prediction latency as the most critical factor impacting accuracy of predictions for this class of branch predictors.

A-optimality orthogonal forward regression algorithm using branch and bound

In this brief, we propose an orthogonal forward regression (OFR) algorithm based on the principles of the branch and bound (BB) and A-optimality experimental design. At each forward regression step, each candidate from a pool of candidate regressors, referred to as S, is evaluated in turn with three possible decisions: 1) one of these is selected and included into the model; 2) some of these remain in S for evaluation in the next forward regression step; and 3) the rest are permanently eliminated from S. Based on the BB principle in combination with an A-optimality composite cost function for model structure determination, a simple adaptive diagnostics test is proposed to determine the decision boundary between 2) and 3). As such the proposed algorithm can significantly reduce the computational cost in the A-optimality OFR algorithm. Numerical examples are used to demonstrate the effectiveness of the proposed algorithm.

Changes in water vapor transports of the ascending branch of the tropical circulation

Recent studies have found contradicting results on whether tropical atmospheric circulation (TAC) has intensified or weakened in recent decades. We here re-investigate recent changes in TAC derived from moisture transports into the tropics using high temporal and spatial resolution reanalyses from ERA-interim. We found a significant strengthening of both, the lower level inward transports and the mid level outward transports over the recent two decades. However the signal in the total budget is weak, because strengthening of the in and outflow neutralize each other, at least to some extent. We found atmospheric humidity to be relatively stable, so suggest that the intensification is mainly caused by an intensification of the wind related circulation strength. The exact quantitative values were found to heavily depend on whether the calculations are based on mean or instantaneous values. We highlight the importance for using the instantaneous ones for transport calculations, as they represent the coincidence of high wind speeds and high atmospheric humidity.

Modelling phosphorus dynamics in multi-branch river systems: A study of the Black River, Lake Simcoe, Ontario, Canada

High rates of nutrient loading from agricultural and urban development have resulted in surface water eutrophication and groundwater contamination in regions of Ontario. In Lake Simcoe (Ontario, Canada), anthropogenic nutrient contributions have contributed to increased algal growth, low hypolimnetic oxygen concentrations, and impaired fish reproduction. An ambitious programme has been initiated to reduce phosphorus loads to the lake, aiming to achieve at least a 40% reduction in phosphorus loads by 2045. Achievement of this target necessitates effective remediation strategies, which will rely upon an improved understanding of controls on nutrient export from tributaries of Lake Simcoe as well as improved understanding of the importance of phosphorus cycling within the lake. In this paper, we describe a new model structure for the integrated dynamic and process-based model INCA-P, which allows fully-distributed applications, suited to branched river networks. We demonstrate application of this model to the Black River, a tributary of Lake Simcoe, and use INCA-P to simulate the fluxes of P entering the lake system, apportion phosphorus among different sources in the catchment, and explore future scenarios of land-use change and nutrient management to identify high priority sites for implementation of watershed best management practises.

Contributory negligence involving overseas European banks in property valuation negligence cases in the UK

This paper examines the phenomenon of cross-border property lending and examines a number of issues regarding lending procedures and decision making processes in the context of the relationship between lender and professional advisor. It commences by placing these procedures and processes in the context of the development of cross border European property investment and finance. The UK has been a popular destination for overseas investors and lenders over the last decade and is therefore used as a case study to examine the additional institutional risk that overseas lenders may face when operating outside of their own country and obtaining advice from home professionals. The UK market was the subject of a boom period during the late 1980s, followed by a recession in the early 1990s. The losses triggered a number of professional negligence actions by lenders against valuers. These include a number of overseas lenders mainly from Europe and these cases have been examined for any particular features which, coupled with other data gained from overseas lenders as part of an interview survey, could be used to isolate any significant problems for European lenders in overseas markets. The research identified a lack of clarity in roles and relationships between lender and advisor, difficulties in communications both internally and between overseas branches and headquarters and failures in provision and interpretation of advice. The paper concludes by identifying the issues which may need to be addressed generally by lenders and their advisors, when the lenders are operating in overseas markets.

Investigation into the adoption intention of social CRM in Saudi banks

The growth of Web 2.0 generation will have influence on developing strong relationships with customers. Even though Web 2.0 technologies and applications have gained significant attention recently by academics and practitioners, research into its potential integration with CRM system remains a poorly investigated subject. This paper aims to investigate the adoption intention of social CRM system, focusing on Saudi banks. A conceptual model was proposed based on technology organisation and environment (TOE) framework. A qualitative approach was applied to validate the research model. The finding suggests that technology infrastructure, and competitive pressures tend to be the most influential drivers to adopt social CRM. In contrast, the limited number of IT experts, security concerns, and organisational structure were found to negatively affect social CRM adoption intention.

On the application of optimal wavelet filter banks for ECG signal classification

This paper discusses ECG signal classification after parametrizing the ECG waveforms in the wavelet domain. Signal decomposition using perfect reconstruction quadrature mirror filter banks can provide a very parsimonious representation of ECG signals. In the current work, the filter parameters are adjusted by a numerical optimization algorithm in order to minimize a cost function associated to the filter cut-off sharpness. The goal consists of achieving a better compromise between frequency selectivity and time resolution at each decomposition level than standard orthogonal filter banks such as those of the Daubechies and Coiflet families. Our aim is to optimally decompose the signals in the wavelet domain so that they can be subsequently used as inputs for training to a neural network classifier.

A parallel formulation for the simulation of a generic branch predictor

A parallel formulation for the simulation of a branch prediction algorithm is presented. This parallel formulation identifies independent tasks in the algorithm which can be executed concurrently. The parallel implementation is based on the multithreading model and two parallel programming platforms: pthreads and Cilk++. Improvement in execution performance by up to 7 times is observed for a generic 2-bit predictor in a 12-core multiprocessor system.