Thermodynamic Computing (1911.01968v2)

Abstract: The hardware and software foundations laid in the first half of the 20th Century enabled the computing technologies that have transformed the world, but these foundations are now under siege. The current computing paradigm, which is the foundation of much of the current standards of living that we now enjoy, faces fundamental limitations that are evident from several perspectives. In terms of hardware, devices have become so small that we are struggling to eliminate the effects of thermodynamic fluctuations, which are unavoidable at the nanometer scale. In terms of software, our ability to imagine and program effective computational abstractions and implementations are clearly challenged in complex domains. In terms of systems, currently five percent of the power generated in the US is used to run computing systems - this astonishing figure is neither ecologically sustainable nor economically scalable. Economically, the cost of building next-generation semiconductor fabrication plants has soared past $10 billion. All of these difficulties - device scaling, software complexity, adaptability, energy consumption, and fabrication economics - indicate that the current computing paradigm has matured and that continued improvements along this path will be limited. If technological progress is to continue and corresponding social and economic benefits are to continue to accrue, computing must become much more capable, energy efficient, and affordable. We propose that progress in computing can continue under a united, physically grounded, computational paradigm centered on thermodynamics. Herein we propose a research agenda to extend these thermodynamic foundations into complex, non-equilibrium, self-organizing systems and apply them holistically to future computing systems that will harness nature's innate computational capacity. We call this type of computing "Thermodynamic Computing" or TC.

• The paper introduces thermodynamic computing as a paradigm where energy dissipation and stochastic processes enable more efficient, adaptive computation.
• It develops a framework integrating non-equilibrium thermodynamics with self-organizing principles to tackle limitations of digital logic systems.
• The research outlines avenues for implementing TC through simulation models, novel materials, and hybrid architectures to enhance performance.

Thermodynamic Computing: A New Paradigm for Future Computing Systems

The concept of thermodynamic computing, as examined and articulated in the referenced report, proposes a radical shift from the existing paradigms of digital computation by framing it within the context of thermodynamics. This paper, stemming from a workshop supported by the National Science Foundation, posits that current computing paradigms, founded on symbol manipulation and logic gate operation, face significant challenges due to thermodynamic fluctuations at the nanoscale, rising energy consumption, and economic impracticalities given the immense costs of semiconductor fabrication facilities.

The report discusses the potential of thermodynamic computing (TC) as a pathway to overcoming these barriers, offering a vision for a computational paradigm that leverages thermodynamics not only as a constraint but also as a fundamental framework. This approach deviates from classical computation by allowing systems to utilize stochastic events and self-organization, akin to processes observed in natural systems which operate efficiently and adaptively.

Key Concepts and Scientific Challenges

Central to the ideas of thermodynamic computing discussed in the report is the recognition of computation as a physical process inherently driven by energy dissipation mechanics. Unlike current paradigms that often seek to mitigate the effects of thermodynamic fluctuations, TC could exploit these for computational benefits, enhancing energy efficiency and adapting to changes in the environment akin to biological systems.

Key scientific challenges are outlined, focusing on developing a comprehensive theory integrating non-equilibrium thermodynamics and understanding how self-organization could be engineered into TC systems. These challenges are necessary to build systems capable of dynamically evolving and harnessing stochasticity to solve tasks more efficiently than current methodologies allow.

Proposed Research Directions

The report delineates several research directions crucial for the evolution of TC systems. These include:

• Core Theoretical Development: Expanding knowledge in fluctuation theorems and thermodynamics to form the theoretical underpinning of TC.
• Model System Development: Creating simulations and prototypes, possibly using components like memristors, that demonstrate the principles of TC.
• Building Blocks: Discovery of new materials and devices that could constitute the architecture of TC systems.
• TC System Architectures: Developing comprehensive languages and frameworks to describe and evaluate TC systems.

Potential Applications and Future Directions

Applications of thermodynamic computing are foreseen in domains that benefit from optimization and intrinsic stochasticity such as machine learning and the simulation of complex systems. TCs promise to dramatically increase efficiency and performance, potentially achieving feats like simulating cognitive structures such as neural networks at a scale comparable to biological entities, offering unprecedented computational capabilities.

The integration of TC may extend to hybrid systems that combine TC with quantum computing elements, capitalizing on the unique properties of each domain. This could lead to advances in fields requiring massive computation power, such as climate modeling, genomics, and even the development of generalized artificial intelligence frameworks.

Conclusion

The proposition of thermodynamic computing represents a forward-looking perspective in the evolution of computational technologies, addressing both the inefficiencies and limitations inherent in the current paradigm. While the execution of such a vision necessitates overcoming substantial scientific and technological hurdles, the potential benefits in terms of performance, energy use, and new problem-solving capabilities present compelling reasons to pursue this innovative research direction. The insights from thermodynamics could serve as a bridge to not only improved computational systems but also enrich our understanding of computation as a physical, energy-driven process.