Computer Arithmetic Algorithms
Computer Arithmetic Algorithms
IEEE Transactions on Computers
Dynamically Exploiting Narrow Width Operands to Improve Processor Power and Performance
HPCA '99 Proceedings of the 5th International Symposium on High Performance Computer Architecture
Variable latency speculative addition: a new paradigm for arithmetic circuit design
Proceedings of the conference on Design, automation and test in Europe
High-Level Synthesis: from Algorithm to Digital Circuit
High-Level Synthesis: from Algorithm to Digital Circuit
Low-Power High-Level Synthesis for Nanoscale CMOS Circuits
Low-Power High-Level Synthesis for Nanoscale CMOS Circuits
A new speculative addition architecture suitable for two's complement operations
Proceedings of the Conference on Design, Automation and Test in Europe
Variable-latency design by function speculation
Proceedings of the Conference on Design, Automation and Test in Europe
Telescopic units: a new paradigm for performance optimization of VLSI designs
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Integrating variable-latency components into high-level synthesis
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Data-Flow Transformations to Maximize the Use of Carry-Save Representation in Arithmetic Circuits
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
A Distributed Controller for Managing Speculative Functional Units in High Level Synthesis
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
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Multispeculative Functional Units (MSFUs) are arithmetic functional units that operate using several predictors for the carry signal. The carry prediction helps to shorten the critical path of the functional unit. The average performance of these units is determined by the hit rate of the prediction. In spite of utilizing more than one predictor, none or only one additional cycle is enough for producing the correct result in the majority of the cases. In this paper we present multispeculation as a way of increasing the performance of tree structures with a negligible area penalty. By judiciously introducing these structures into computation trees, it will only be necessary to predict in certain selected nodes, thus minimizing the number of operations that can potentially mispredict. Hence, the average latency will be diminished and thus performance will be increased. Our experiments show that it is possible to improve on average 24% and 38% execution time, when considering logarithmic and linear modules, respectively.