English
Related papers

Related papers: Integrated photonic neuromorphic computing: device…

200 papers

Rapid advancements in deep learning over the past decade have fueled an insatiable demand for efficient and scalable hardware. Photonics offers a promising solution by leveraging the unique properties of light. However, conventional neural…

As robots become smarter and more ubiquitous, optimizing the power consumption of intelligent compute becomes imperative towards ensuring the sustainability of technological advancements. Neuromorphic computing hardware makes use of…

The value of brain-inspired neuromorphic computers critically depends on our ability to program them for relevant tasks. Currently, neuromorphic hardware often relies on machine learning methods adapted from deep learning. However,…

Neural and Evolutionary Computing · Computer Science 2024-10-31 Steven Abreu , Jens E. Pedersen

Quantum technologies, such as quantum communication, sensing and imaging, need a platform which is flexible, miniaturizable and works at room temperature. Integrated photonics is a promising and fast-developing platform. This requires to…

Quantum Physics · Physics 2021-10-12 Andrei-Emanuel Dragomir , Cristian George Ivan , Radu Ionicioiu

Photonic computing shows great potential for signal processing and artificial intelligence (AI) acceleration due to its ultra-high speed, low energy consumption, and inherent parallelism. Existing photonic computing research has mainly…

Neuromorphic computing promises to transform the current paradigm of traditional computing towards Non-Von Neumann dynamic energy-efficient problem solving. Thus, dynamic memory devices capable of simultaneously performing nonlinear…

Neuromorphic computing is a non-von Neumann computing paradigm that performs computation by emulating the human brain. Neuromorphic systems are extremely energy-efficient and known to consume thousands of times less power than CPUs and…

Neural and Evolutionary Computing · Computer Science 2021-04-30 Prasanna Date , Catherine Schuman , Bill Kay , Thomas Potok

Due to challenging efficiency limits facing conventional and unconventional electronic architectures, information processors based on photonics have attracted renewed interest. Research communities have yet to settle on definitive…

Optics · Physics 2022-05-19 Alexander N. Tait

Software-implementation, via neural networks, of brain-inspired computing approaches underlie many important modern-day computational tasks, from image processing to speech recognition, artificial intelligence and deep learning…

Optics · Physics 2021-02-19 J. Feldmann , N. Youngblood , C. D. Wright , H. Bhaskaran , W. H. P. Pernice

DSP (digital signal processing) has been widely applied in optical communication systems to mitigate signal distortions and has become one of the key technologies that have sustained data traffic growth over the past decade. However, the…

Current AI governance frameworks, including regulatory benchmarks for accuracy, latency, and energy efficiency, are built for static, centrally trained artificial neural networks on von Neumann hardware. NeuroAI systems, embodied in…

Emerging Technologies · Computer Science 2026-02-06 Afifah Kashif , Abdul Muhsin Hameed , Asim Iqbal

Emergent nanoscale non-volatile memory technologies with high integration density offer a promising solution to overcome the scalability limitations of CMOS-based neural networks architectures, by efficiently exhibiting the key principle of…

Hardware Architecture · Computer Science 2018-11-14 Saber Moradi , Rajit Manohar

Photonic computing is a computing paradigm which have great potential to overcome the energy bottlenecks of electronic von Neumann architecture. Throughput and power consumption are fundamental limitations of…

Emerging Technologies · Computer Science 2026-04-06 Saurabh Ranjan , Sonika Thakral , Amit Sehgal

Deep neural networks with applications from computer vision and image processing to medical diagnosis are commonly implemented using clock-based processors, where computation speed is limited by the clock frequency and the memory access…

Emerging Technologies · Computer Science 2022-07-06 Farshid Ashtiani , Alexander J. Geers , Firooz Aflatouni

AI/ML for data centres and data centres for AI/ML are defining new trends in cloud computing. Disaggregated heterogeneous reconfigurable computing systems realized by photonic interconnects and photonic switching expect greatly enhanced…

Networking and Internet Architecture · Computer Science 2022-09-20 S. J. Ben Yoo

Neuromorphic photonic accelerators are becoming increasingly popular, since they can significantly improve computation speed and energy efficiency, leading to femtojoule per MAC efficiency. However, deploying existing DL models on such…

Emerging Technologies · Computer Science 2023-10-03 Manos Kirtas , Nikolaos Passalis , Nikolaos Pleros , Anastasios Tefas

The scalability of modern computing hardware is limited by physical bottlenecks and high energy consumption. These limitations could be addressed by neuromorphic hardware (NMH) which is inspired by the human brain. NMH enables physically…

Emerging Technologies · Computer Science 2023-01-25 Can Rager , Kyle Webster

Photons have been a flagship system for studying quantum mechanics, advancing quantum information science, and developing quantum technologies. Quantum entanglement, teleportation, quantum key distribution and early quantum computing…

Quantum Physics · Physics 2019-12-12 Sergei Slussarenko , Geoff J. Pryde

Rapidly growing demands for fast information processing have launched a race for creating compact and highly efficient optical devices that can reliably transmit signals without losses. Recently discovered topological phases of light…

Optics · Physics 2020-06-04 Daria Smirnova , Daniel Leykam , Yidong Chong , Yuri Kivshar

We review the recent advances reported in the field of integrated photonic waveguide meshes, both from the theoretical as well as from the experimental point of view. We show how these devices can be programmed to implement both traditional…

Applied Physics · Physics 2019-03-13 Daniel Perez , Ivana Gasulla , Jose Capmany