U-DVS SRAM design considerations

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.Includes bibliographical references (leaves 73-78).With the continuous scaling down of transistor feature sizes, the semiconductor industry faces new challenges. One of these challenges is the incessant increase of power consumption in integrated circuits. This problem has motivated the industry and academia to pay significant attention to low-power circuit design for the past two decades. Operating digital circuits at lower voltage levels was shown to increase energy efficiency and lower power consumption. Being an integral part of the digital systems, Static Random Access Memories (SRAMs), dominate the power consumption and area of modern integrated circuits. Consequently, designing low-power high density SRAMs operational at low voltage levels is an important research problem. This thesis focuses on and makes several contributions to low-power SRAM design. The trade-offs and potential overheads associated with designing SRAMs for a very large voltage range are analyzed. An 8T SRAM cell is designed and optimized for both sub-threshold and above-threshold operation. Hardware reconfigurability is proposed as a solution to power and area overheads due to peripheral assist circuitry which are necessary for low voltage operation. A 64kbit SRAM has been designed in 65nm CMOS process and the fabricated chip has been tested, demonstrating operation at power supply levels from 0.25V to 1.2V. This is the largest operating voltage range reported in 65nm semiconductor technology node. Additionally, another low voltage SRAM has been designed for the on-chip caches of a low-power H.264 video decoder. Power and performance models of the memories have been developed along with a configurable interface circuit. This custom memory implemented with the low-power architecture of the decoder provides nearly 10X power savings.by Mahmut E. Sinangil.S.M

Low-power and application-specific SRAM design for energy-efficient motion estimation

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 181-189).Video content is expected to account for 70% of total mobile data traffic in 2015. High efficiency video coding, in this context, is crucial for lowering the transmission and storage costs for portable electronics. However, modern video coding standards impose a large hardware complexity. Hence, energy-efficiency of these hardware blocks is becoming more critical than ever before for mobile devices. SRAMs are critical components in almost all SoCs affecting the overall energy-efficiency. This thesis focuses on algorithm and architecture development as well as low-power and application-specific SRAM design targeting motion estimation. First, a motion estimation design is considered for the next generation video standard, HEVC. Hardware cost and coding efficiency trade-offs are quantified and an optimum design choice between hardware complexity and coding efficiency is proposed. Hardware-efficient search algorithm, shared search range across CU engines and pixel pre-fetching algorithms provide 4.3x area, 56x on-chip bandwidth and 151 x off-chip bandwidth reduction. Second, a highly-parallel motion estimation design targeting ultra-low voltage operation and supporting AVC/H.264 and VC-1 standards are considered. Hardware reconfigurability along with frame and macro-block parallel processing are implemented for this engine to maximize hardware sharing between multiple standards and to meet throughput constraints. Third, in the context of low-power SRAMs, a 6T and an 8T SRAM are designed in 28nm and 45nm CMOS technologies targeting low voltage operation. The 6T design achieves operation down to 0.6V and the 8T design achieves operation down to 0.5V providing ~ 2.8x and ~ 4.8x reduction in energy/access respectively. Finally, an application-specific SRAM design targeted for motion estimation is developed. Utilizing the correlation of pixel data to reduce bit-line switching activity, this SRAM achieves up to 1.9x energy savings compared to a similar conventional 8T design. These savings demonstrate that application-specific SRAM design can introduce a new dimension and can be combined with voltage scaling to maximize energy-efficiency.by Mahmut Ersin Sinangil.Ph.D

Self-aware Computing in the Angstrom Processor

Addressing the challenges of extreme scale computing requires holistic design of new programming models and systems that support those models. This paper discusses the Angstrom processor, which is designed to support a new Self-aware Computing (SEEC) model. In SEEC, applications explicitly state goals, while other systems components provide actions that the SEEC runtime system can use to meet those goals. Angstrom supports this model by exposing sensors and adaptations that traditionally would be managed independently by hardware. This exposure allows SEEC to coordinate hardware actions with actions specified by other parts of the system, and allows the SEEC runtime system to meet application goals while reducing costs (e.g., power consumption).United States. Defense Advanced Research Projects Agency. The Ubiquitous High Performance Computing Progra