493 research outputs found
Stochastic Computing with Integrated Optics
Stochastic computing (SC) allows reducing hardware complexity and improving
energy efficiency of error resilient applications. However, a main limitation
of the computing paradigm is the low throughput induced by the intrinsic serial
computing of bit-streams. In this paper, we address the implementation of SC in
the optical domain, with the aim to improve the computation speed. We implement
a generic optical architecture allowing the execution of polynomial functions.
We propose design methods to explore the design space in order to optimize key
metrics such as circuit robustness and power consumption. We show that a
circuit implementing a 2 nd order polynomial degree function and operating at
1Ghz leads to 20.1pJ laser consumption per computed bit
Integrated Photonic Tensor Processing Unit for a Matrix Multiply: a Review
The explosion of artificial intelligence and machine-learning algorithms,
connected to the exponential growth of the exchanged data, is driving a search
for novel application-specific hardware accelerators. Among the many, the
photonics field appears to be in the perfect spotlight for this global data
explosion, thanks to its almost infinite bandwidth capacity associated with
limited energy consumption. In this review, we will overview the major
advantages that photonics has over electronics for hardware accelerators,
followed by a comparison between the major architectures implemented on
Photonics Integrated Circuits (PIC) for both the linear and nonlinear parts of
Neural Networks. By the end, we will highlight the main driving forces for the
next generation of photonic accelerators, as well as the main limits that must
be overcome
The Boston University Photonics Center annual report 2016-2017
This repository item contains an annual report that summarizes activities of the Boston University Photonics Center in the 2016-2017 academic year. The report provides quantitative and descriptive information regarding photonics programs in education, interdisciplinary research, business innovation, and technology development. The Boston University Photonics Center (BUPC) is an interdisciplinary hub for education, research, scholarship, innovation, and technology development associated with practical uses of light.This has undoubtedly been the Photonics Center’s best year since I became Director 10 years ago. In the following pages, you will see highlights of the Center’s activities in the past year, including more than 100 notable scholarly publications in the leading journals in our field, and the attraction of more than 22 million dollars in new research grants/contracts. Last year I had the honor to lead an international search for the first recipient of the Moustakas Endowed Professorship in Optics and Photonics, in collaboration with ECE Department Chair Clem Karl. This professorship honors the Center’s most impactful scholar and one of the Center’s founding visionaries, Professor Theodore Moustakas. We are delighted to haveawarded this professorship to Professor Ji-Xin Cheng, who joined our faculty this year.The past year also marked the launch of Boston University’s Neurophotonics Center, which will be allied closely with the Photonics Center. Leading that Center will be a distinguished new faculty member, Professor David Boas. David and I are together leading a new Neurophotonics NSF Research Traineeship Program that will provide $3M to promote graduate traineeships in this emerging new field. We had a busy summer hosting NSF Sites for Research Experiences for Undergraduates, Research Experiences for Teachers, and the BU Student Satellite Program. As a community, we emphasized the theme of “Optics of Cancer Imaging” at our annual symposium, hosted by Darren Roblyer. We entered a five-year second phase of NSF funding in our Industry/University Collaborative Research Center on Biophotonic Sensors and Systems, which has become the centerpiece of our translational biophotonics program. That I/UCRC continues to focus on advancing the health care and medical device industries
Computational Scaling in Inverse Photonic Design Through Factorization Caching
Inverse design coupled with adjoint optimization is a powerful method to
design on-chip nanophotonic devices with multi-wavelength and multi-mode
optical functionalities. Although only two simulations are required in each
iteration of this optimization process, these simulations still make up the
vast majority of the necessary computations, and render the design of complex
devices with large footprints computationally infeasible. Here, we introduce a
multi-faceted factorization caching approach to drastically simplify the
underlying computations in finite-difference frequency-domain (FDFD)
simulations, and significantly reduce the time required for device
optimization. Specifically, we cache the symbolic and numerical factorizations
for the solution of the corresponding system of linear equations in discretized
FDFD simulations, and re-use them throughout the entire device design process.
As proof-of-concept demonstrations of the resulting computational advantage, we
present simulation speedups reaching as high as in the design of
broadband wavelength and mode multiplexers compared to conventional FDFD
methods. We also show that factorization caching scales well over a broad range
of footprints independent of the device geometry, from as small as to over . Our results present significant enhancements in
the computational efficiency of inverse photonic design, and can greatly
accelerate the use of machine-optimized devices in future photonic systems
Recommended from our members
Network-on-Chip Synchronization
Technology scaling has enabled the number of cores within a System on Chip (SoC) to increase significantly. Globally Asynchronous Locally Synchronous (GALS) systems using Dynamic Voltage and Frequency Scaling (DVFS) operate each of these cores on distinct and dynamic clock domains. The main communication method between these cores is increasingly more likely to be a Network-on-Chip (NoC). Typically, the interfaces between these clock domains experience multi-cycle synchronization latencies due to their use of “brute-force” synchronizers. This dissertation aims to improve the performance of NoCs and thereby SoCs as a whole by reducing this synchronization latency.
First, a survey of NoC improvement techniques is presented. One such improvement technique: a multi-layer NoC, has been successfully simulated. Given how one of the most commonly used techniques is DVFS, a thorough analysis and simulation of brute-force synchronizer circuits in both current and future process technologies is presented. Unfortunately, a multi-cycle latency is unavoidable when using brute-force synchronizers, so predictive synchronizers which require only a single cycle of latency have been proposed.
To demonstrate the impact of these predictive synchronizer circuits at a high level, multi-core system simulations incorporating these circuits have been completed. Multiple forms of GALS NoC configurations have been simulated, including multi-synchronous, NoC-synchronous, and single-synchronizer. Speedup on the SPLASH benchmark suite was measured to directly quantify the performance benefit of predictive synchronizers in a full system. Additionally, Mean Time Between Failures (MTBF) has been calculated for each NoC synchronizer configuration to determine the reliability benefit possible when using predictive synchronizers
- …