Related papers: Efficient Superconductor Arithmetic Logic Unit for…
We have repurposed Google Tensor Processing Units (TPUs), application-specific chips developed for machine learning, into large-scale dense linear algebra supercomputers. The TPUs' fast inter-core interconnects (ICI)s, physically…
One of the main, long-term objectives of artificial intelligence is the creation of thinking machines. To that end, substantial effort has been placed into designing cognitive systems; i.e. systems that can manipulate semantic-level…
Reducing delay, power consumption, and chip area of a logic circuit are the main targets of a designer. Most of the times, the designer sacrifices power consumption and chip area to improve delay for a given technology node. To overcome…
Gate-level clocking, typical in traditional approaches to Single Flux Quantum (SFQ) technology, makes the effective synthesis of superconducting circuits a significant engineering hurdle. This paper addresses this challenge by employing the…
A quantum computer can solve hard problems - such as prime factoring, database searching, and quantum simulation - at the cost of needing to protect fragile quantum states from error. Quantum error correction provides this protection, by…
As the emerging field of machine learning, deep learning shows excellent ability in solving complex learning problems. However, the size of the networks becomes increasingly large scale due to the demands of the practical applications,…
The logarithmic number system (LNS) is arguably not broadly used due to exponential circuit overheads for summation tables relative to arithmetic precision. Methods to reduce this overhead have been proposed, yet still yield designs with…
We present the fabrication and characterization of transmon qubits formed from aluminum Josephson junctions on two different silicon-based substrates: (i) high-resistivity silicon (Si) and (ii) silicon-on-insulator (SOI). Key to the qubit…
Neural networks have to capture mathematical relationships in order to learn various tasks. They approximate these relations implicitly and therefore often do not generalize well. The recently proposed Neural Arithmetic Logic Unit (NALU) is…
The processing unit of a solid-state quantum computer consists in an array of coupled qubits, each locally driven with on-chip microwave lines that route carefully-engineered control signals to the qubits in order to perform logical…
In this paper, a fault-tolerant approach to mitigate transient and permanent faults of arithmetic and logic operations of embedded processors called FT-EALU is proposed. In this method, each operation is replicated in time and the derived…
In electronic design automation, logic optimization operators play a crucial role in minimizing the gate count of logic circuits. However, their computation demands are high. Operators such as refactor conventionally form iterative cuts for…
This paper describes JANUS, a modular massively parallel and reconfigurable FPGA-based computing system. Each JANUS module has a computational core and a host. The computational core is a 4x4 array of FPGA-based processing elements with…
Superconducting qubits are one of the most promising candidates to implement quantum computers. The superiority of superconducting quantum computers over any classical device in simulating random but well-determined quantum circuits has…
All-optical integrated circuits for computing and information processing have been pursued for decades as a potential strategy to overcome the speed limitations intrinsic to electronics. However feasible on-chip integrated logic units and…
Modern Neural Network (NN) architectures heavily rely on vast numbers of multiply-accumulate arithmetic operations, constituting the predominant computational cost. Therefore, this paper proposes a high-throughput, scalable and energy…
Fast phase logic (FPL) is a novel digital superconductor electronic (SCE) logic family that employs multiple junction types, including switching 0-Josephson junctions (0-JJs), non-switching 0-JJ stacks, and $\pi$-JJs. FPL enables flexible,…
Aluminum-based Josephson junctions are currently the main sources of nonlinearity for control and manipulation of superconducting qubits. A phase-slip junction, the dual of a Josephson junction, provides an alternative source of…
In February 2014 Time magazine announced to the world that the first quantum computer had been put in use. One key component of this computer is the Josephson-junction, a superconducting device, based on completely different scientific and…
Quantum processing units (QPUs) based on superconducting Josephson junctions promise significant advances in quantum computing. However, they face critical challenges. Decoherence, scalability limitations, and error correction overhead…