Jeremy Schlachter
Orcid: 0000-0003-1483-3591
According to our database1,
Jeremy Schlachter
authored at least 14 papers
between 2015 and 2018.
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Bibliography
2018
Design of Approximate Circuits by Fabrication of False Timing Paths: The Carry Cut-Back Adder.
IEEE J. Emerg. Sel. Topics Circuits Syst., 2018
Hardware Acceleration of HDR-Image Tone Mapping on an FPGA-CPU Platform Through High-Level Synthesis.
Proceedings of the 31st IEEE International System-on-Chip Conference, 2018
2017
IEEE Trans. Very Large Scale Integr. Syst., 2017
A study on the energy-precision tradeoffs on commercially available processors and SoCs with an EPI based energy model.
Proceedings of the 30th IEEE International System-on-Chip Conference, 2017
2016
Overcoming the power wall by exploiting inexactness and emerging COTS architectural features: Trading precision for improving application quality.
Proceedings of the 29th IEEE International System-on-Chip Conference, 2016
Design of energy-efficient discrete cosine transform using pruned arithmetic circuits.
Proceedings of the IEEE International Symposium on Circuits and Systems, 2016
Proceedings of the ESSCIRC Conference 2016: 42<sup>nd</sup> European Solid-State Circuits Conference, 2016
A low-power <i>carry cut-back</i> approximate adder with fixed-point implementation and floating-point precision.
Proceedings of the 53rd Annual Design Automation Conference, 2016
2015
Proceedings of the IEEE 13th International New Circuits and Systems Conference, 2015
Near/Sub-Threshold Circuits and Approximate Computing: The Perfect Combination for Ultra-Low-Power Systems.
Proceedings of the 2015 IEEE Computer Society Annual Symposium on VLSI, 2015
Proceedings of the 2015 IEEE International Symposium on Circuits and Systems, 2015
Energy-efficient inexact speculative adder with high performance and accuracy control.
Proceedings of the 2015 IEEE International Symposium on Circuits and Systems, 2015
Proceedings of the 2015 Design, Automation & Test in Europe Conference & Exhibition, 2015
Opportunities for energy efficient computing: a study of inexact general purpose processors for high-performance and big-data applications.
Proceedings of the 2015 Design, Automation & Test in Europe Conference & Exhibition, 2015