Future Computing: DNA Hard Drives

DNA is a hard drive, the memory in every cell of every living organism that has the instructions on how to make that cell. With the exponential growth of our media, the growth of data storage is also increasing. DNA is incredible compact due to its molecular structure and can be used to achieve data attractively through genome sequencing. A raw limit of 1 Exabyte/mm3 (109 GB/mm3) having half-life of over 500 years. With this, all the data of the world can be stored in just a small place of a room

Photonic Memristor for Future Computing: A Perspective

Photonic computing and neuromorphic computing could address the inherent limitations of traditional von Neumann architecture and gradually invalidate Moore’s law. As photonics applications are capable of storing and processing data in an optical manner with unprecedented bandwidth and high speed, twoâ terminal photonic memristors with a remote optical control of resistive switching behaviors at defined wavelengths ensure the benefit of onâ chip integration, low power consumption, multilevel data storage, and a large variation margin, suggesting promising advantages for both photonic and neuromorphic computing. Herein, the development of photonic memristors is reviewed, as well as their application in photonic computing and emulation on optogeneticsâ modulated artificial synapses. Different photoactive materials acting as both photosensing and storage media are discussed in terms of their opticalâ tunable memory behaviors and underlying resistive switching mechanism with consideration of photogating and photovoltaic effects. Moreover, lightâ involved logic operations, systemâ level integration, and lightâ controlled artificial synaptic memristors along with improved learning tasks performance are presented. Furthermore, the challenges in the field are discussed, such as the lack of a comprehensive understanding of microscopic mechanisms under light illumination and a general constraint of inferior nearâ infrared (NIR) sensitivity.The development of photonic memristors and their application in photonic computing and emulation on optogeneticsâ modulated artificial synapses are reviewed. Photoactive materials as photosensing and storage media are discussed, considering their opticalâ tunable memory behavior and resistive switching mechanism including photogating and photovoltaic effect. Lightâ involved logic operations, system level integration, and artificial synaptic memristors along with improved learning tasks performance are presented.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153103/1/adom201900766.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/153103/2/adom201900766_am.pd

ParaFPGA 2013: Harnessing Programs, Power and Performance in Parallel FPGA applications

Future computing systems will require dedicated accelerators to achieve high-performance. The mini-symposium ParaFPGA explores parallel computing with FPGAs as an interesting avenue to reduce the gap between the architecture and the application. Topics discussed are the power of functional and dataflow languages, the performance of high-level synthesis tools, the automatic creation of hardware multi-cores using C-slow retiming, dynamic power management to control the energy consumption, real-time reconfiguration of streaming image processing filters and memory optimized event image segmentation

HIGH PERFORMANCE SILVER DIFFUSIVE MEMRISTORS FOR FUTURE COMPUTING

Sneak path current is a significant remaining obstacle to the utilization of large crossbar arrays for non-volatile memories and other applications of memristors. A two-terminal selector device with an extremely large current-voltage nonlinearity and low leakage current could solve this problem. We present here a Ag/oxide-based threshold switching (TS) device with attractive features such as high current-voltage nonlinearity (~1010), steep turn-on slope (less than 1 mV/dec), low OFF-state leakage current (~10-14 A), fast turn ON/OFF speeds (\u3c75/250 ns), and good endurance (\u3e108 cycles). The feasibility of using this selector with a typical memristor has been demonstrated by physically integrating them into a multilayered 1S1R cell. Structural analysis of the nanoscale crosspoint device suggests that elongation of a Ag nanoparticle under voltage bias followed by spontaneous reformation of a more spherical shape after power off is responsible for the observed threshold switching of the device. Such mechanism has been quantitatively verified by the Ag nanoparticle dynamics simulation based on thermal diffusion assisted by bipolar electrode effect and interfacial energy minimization

Mass storage system experiences and future needs at the National Center for Atmospheric Research

This presentation is designed to relate some of the experiences of the Scientific Computing Division at NCAR dealing with the 'data problem'. A brief history and a development of some basic Mass Storage System (MSS) principles are given. An attempt is made to show how these principles apply to the integration of various components into NCAR's MSS. There is discussion of future MSS needs for future computing environments