Publications

Abstract not provided.

For more than 50 years, computers have made steady and dramatic improvements, all thanks to Moore’s Law—the exponential increase over time in the number of transistors that can be fabricated on an integrated circuit of a given size. Moore’s Law owed its success to the fact that as transistors were made smaller, they became simultaneously cheaper, faster, and more energy efficient. The payoff from this win-win-win scenario enabled reinvestment in semiconductor fabrication technology that could make even smaller, more densely-packed transistors. And so this virtuous cycle continued, decade after decade. Now though, experts in industry, academia, and government laboratories anticipate that semiconductor miniaturization won’t continue much longer—maybe 10 years or so, at best. Making transistors smaller no longer yields the improvements it used to. The physical characteristics of small transistors forced clock speeds to cease getting faster more than a decade ago, which drove the industry to start building chips with multiple cores. But even multi-core architectures must contend with increasing amounts of “dark silicon,” areas of the chip that must be powered off to avoid overheating.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Information loss from a computation implies energy dissipation due to Landauer’s Principle. Thus, increasing the amount of useful computational work that can be accomplished within a given energy budget will eventually require increasing the degree to which our computing technologies avoid information loss, i.e., are logically reversible. But the traditional definition of logical reversibility is actually more restrictive than is necessary to avoid information loss and energy dissipation due to Landauer’s Principle. As a result, the operations that have traditionally been viewed as the atomic elements of reversible logic, such as Toffoli gates, are not really the simplest primitives that one can use for the design of reversible hardware. Arguably, a complete theoretical framework for reversible computing should provide a more general, parsimonious foundation for practical engineering. To this end, we use a rigorous quantitative formulation of Landauer’s Principle to develop the theory of Generalized Reversible Computing (GRC), which precisely characterizes the minimum requirements for a computation to avoid information loss and the consequent energy dissipation, showing that a much broader range of computations are, in fact, reversible than is acknowledged by traditional reversible computing theory. This paper summarizes the foundations of GRC theory and briefly presents a few of its applications.

Industry's inability to reduce logic gates' energy consumption is slowing growth in an important part of the worldwide economy. Some scientists argue that alternative approaches could greatly reduce energy consumption. These approaches entail myriad technical and political issues.

Abstract not provided.

We address practical limits of energy efficiency scaling for logic and memory. Scaling of logic will end with unreliable operation, making computers probabilistic as a side effect. The errors can be corrected or tolerated, but overhead will increase with further scaling. We address the tradeoff between scaling and error correction that yields minimum energy per operation, finding new error correction methods with energy consumption limits about 2× below current approaches. The maximum energy efficiency for memory depends on several other factors. Adiabatic and reversible methods applied to logic have promise, but overheads have precluded practical use. However, the regular array structure of memory arrays tends to reduce overhead and makes adiabatic memory a viable option. This paper reports an adiabatic memory that has been tested at about 85× improvement over standard designs for energy efficiency. Combining these approaches could set energy efficiency expectations for processor-in-memory computing systems.

Continuing to improve computational energy efficiency will soon require developing and deploying new operational paradigms for computation that circumvent the fundamental thermodynamic limits that apply to conventionally-implemented Boolean logic circuits. In particular, Landauer's principle tells us that irreversible information erasure requires a minimum energy dissipation of kT ln 2 per bit erased, where k is Boltzmann's constant and T is the temperature of the available heat sink. However, correctly applying this principle requires carefully characterizing what actually constitutes "information erasure" within a given physical computing mechanism. In this paper, we show that abstract combinational logic networks can validly be considered to contain no information beyond that specified in their input, and that, because of this, appropriately-designed physical implementations of even multi-layer networks can in fact be updated in a single step while incurring no greater theoretical minimum energy dissipation than is required to update their inputs. Furthermore, this energy can approach zero if the network state is updated adiabatically via a reversible transition process. Our novel operational paradigm for updating logic networks suggests an entirely new class of hardware devices and circuits that can be used to reversibly implement Boolean logic with energy dissipation far below the Landauer limit.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.