Shivam Goyal

Work place: JECRC University, Jaipur, Rajasthan 303905, India

E-mail: shivamgoyal.sg05@gmail.com

Website:

Research Interests: Computer Architecture and Organization, Computing Platform, Data Structures and Algorithms

Biography

Shivam Goyal is currently an M.Sc. candidate in the Department of Electronics and Communication Engineering at JECRC University at Jaipur (India). He did his B.Tech in Electronics and Communication Engineering from JECRC UDML College of engineering, Jaipur, India. His research interests include high-performance computing and Microarchitecture.

Author Articles
Two-Level Alloyed Branch Predictor based on Genetic Algorithm for Deep Pipelining

By Shivam Goyal Jaskirat Singh

DOI: https://doi.org/10.5815/ijmecs.2017.05.04, Pub. Date: 8 May 2017

To gain improved performance in multiple issue superscalar processors, the increment in instruction fetch and issue rate is pretty necessary. Evasion of control hazard is a primary source to get peak instruction level parallelism in superscalar processors. Conditional branch prediction can help in improving the performance of processors only when these predictors are equipped with algorithms to give higher accuracy. The Increment in single miss-prediction rate can cause wastage of more than 20% of the instructions cycles, which leads us to an exploration of new techniques and algorithms that increase the accuracy of branch prediction. Alloying is a way to exploit the local and global history of different predictors in the same structure and sometimes also called hybrid branch prediction. In this paper, we aim to design a more accurate and robust two-level alloyed predictor, whose behavior is more dynamic on changing branch direction.

 

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