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Circuit knitting Based On Quasiprobability Simulation


New paper "Circuit knitting with classical communication, " from researchers at ETH Zurich and IBM Quantum. Abstract: "The scarcity of qubits is a major obstacle to the practical usage of quantum computers in the near future. To circumvent this problem, various circuit knitting techniques have been developed to partition large quantum circuits into subcircuits that fit on smaller devices,... » read more

Power/Performance Bits: Dec. 21


Compact optical amplifier Researchers at Chalmers University of Technology propose a new optical amplifier design that is compact, high-performance, and doesn't generate excess noise. “We have developed the world's first optical amplifier that significantly enhances the range, sensitivity and performance of optical communication, that does not generate any excess noise – and is also com... » read more

Accelerating Inference of Convolutional Neural Networks Using In-memory Computing


Abstract: "In-memory computing (IMC) is a non-von Neumann paradigm that has recently established itself as a promising approach for energy-efficient, high throughput hardware for deep learning applications. One prominent application of IMC is that of performing matrix-vector multiplication in (1) time complexity by mapping the synaptic weights of a neural-network layer to the devices of an ... » read more

Power/Performance Bits: Feb. 23


Photonic AI accelerator There are now many processors and accelerators focused on speeding up neural network performance, but researchers at the University of Münster, University of Oxford, Swiss Federal Institute of Technology Lausanne (EPFL), IBM Research Europe, and University of Exeter say AI processing could happen even faster with the use of photonic tensor processors that can handle mu... » read more