Lucian N. Vintan

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The main aim of this short paper is to propose a new branch prediction approach called by us "neural branch prediction". We developed a first neural predictor model based on a simple neural learning algorithm, known as Learning Vector Quantization algorithm. Based on a trace driven simulation method we investigated the influences of the learning step and(More)
Dynamic branch prediction in high-performance processors is a specific instance of a general Time Series Prediction problem that occurs in many areas of science. In contrast, most branch prediction research focuses on Two-Level Adaptive Branch Prediction techniques, a very specific solution to the branch prediction problem. An alternative approach is to(More)
Through this paper we developed an alternative approach to the present -- day two level dynamic branch prediction structures. Instead of predicting branches based on history information, we propose to pre - calculate the branch outcome. A pre - calculated branch prediction (PCB) determines the outcome of a branch as soon as all of the branch's operands are(More)
Dynamic branch prediction in high-performance processors is a specific instance of a general time series prediction problem that occurs in many areas of science. Most branch prediction research focuses on two-level adaptive branch prediction techniques, a very specific solution to the branch prediction problem. An alternative approach is to look to other(More)
The majority of currently available branch predictors base their prediction accuracy on the previous k branch outcomes. Such predictors sustain high prediction accuracy but they do not consider the impact of unbiased branches which are difficult-to-predict. In this paper, we quantify and evaluate the impact of unbiased branches and show that any gain in(More)
This paper presents a design space exploration of a selective <i>load value prediction scheme</i> suitable for energy-aware Simultaneous Multi-Threaded (SMT) architectures. A load value predictor is an architectural enhancement which speculates over the results of a micro-processor <i>load</i> instruction to speed-up the execution of the following(More)
The computing systems, and particularly microarchitectures, are in a continuous expansion reaching an unmanageable complexity by the human mind. In order to understand and control this expansion, researchers need to design and implement larger and more complex systems’ simulators. In the current paradigm the simulators play the key role in going further, by(More)
The majority of currently available dynamic branch predictors base their prediction accuracy on the previous k branch outcomes. Such predictors sustain high prediction accuracy but they do not consider the impact of unbiased branches, which are difficult-to-predict. In this paper, we evaluate the impact of unbiased branches in terms of prediction accuracy(More)
In our previously published research we discovered some very difficult to predict branches, called unbiased branches. Since the overall performance of modern processors is seriously affected by misprediction recovery, especially these difficult branches represent a source of important performance penalties. Our statistics show that about 28% of branches are(More)