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Superconductor electronics (SCE) promise computer systems with orders of magnitude higher speeds and lower energy consumption than their complementary metal–oxide semiconductor (CMOS) counterparts. At the same time, the scalability and resource utilization of superconducting systems are major concerns. Some of these concerns come from device-level challenges and the gap between SCE and CMOS technology nodes, and others come from the way Josephson junctions (JJs) are used. Toward this end, we notice that a considerable fraction of hardware resources are not involved in logic operations, but rather are used for fan-out and buffering purposes. In this article, we ask if there is a way to reduce these overheads, propose the use of JJs at the cell boundaries to increase the number of outputs that a single stage can drive, and establish a set of rules to discretize critical currents in a way that is conducive to this assignment. Finally, we explore the design trade-offs that the presented approach opens up and demonstrate its promise through detailed analog simulations and modeling analyses. Our experiments indicate that the introduced method leads to a 48% savings in the JJ count for a tree with a fan-out of 1024, as well as an average of 43% of the JJ count for signal splitting and 32% for clock splitting in ISCAS’85 benchmarks. 

When extremely low-energy processing is required, the choice of data representation makes a tremendous difference. Each representation (e.g., frequency domain, residue coded, and log-scale) embodies a different set of tradeoffs based on the algebraic operations that are either easy or hard to perform in that domain. We demonstrate the potential of a novel form of encoding, race logic, in which information is represented as the delay in the arrival of a signal. Under this encoding, the ways in which signal delays interact and interfere with one another define the operation of the system. Observations of the relative delays (for example, the outcome of races between signals) define the output of the computation. Interestingly, completely standard hardware logic elements can be repurposed to this end and the resulting embedded systems have the potential to be extremely energy efficient. To realize this potential in a practical design, we demonstrate two different approaches to the creation of programmable tree-based ensemble classifiers in an extended set of race logic primitives; we explore the trade-offs inherent to their operation across sensor, hardware architecture, and algorithm; and we compare the resulting designs against traditional state-of-the-art hardware techniques. 

As computer architecture continues to expand beyond software-agnostic microarchitecture to data center organization, reconfigurable logic, heterogeneous systems, application-specific logic, and even radically different technologies such as quantum computing, detailed cycle-level simulation is no longer presupposed. Exploring designs under such complex interacting relationships (e.g., performance, energy, thermal, cost, voltage, frequency, cooling energy, leakage, etc.) calls for a more integrative but higher-level approach. We propose Charm, a domain specific language supporting Closed-form High-level ARchitecture Modeling. Charm enables mathematical representations of mutually dependent architectural relationships to be specified, composed, checked, evaluated and reused. The language is interpreted through a combination of symbolic evaluation (e.g., restructuring) and compiler techniques (e.g., memoization and invariant hoisting), generating executable evaluation functions and optimized analysis procedures. Further supporting reuse, a type system constrains architectural quantities and ensures models operate only in a validated domain. Through two case studies, we demonstrate that Charm allows one to define high-level architecture models concisely, maximize reusability, capture unreasonable assumptions and inputs, and significantly speedup design space exploration.