Results 91 to 100 of about 193,534 (289)

Hardware Accelerated Compression of LIDAR Data Using FPGA Devices

Sensors, 2013
Airborne Light Detection and Ranging (LIDAR) has become a mainstream technology for terrain data acquisition and mapping. High sampling density of LIDAR enables the acquisition of high details of the terrain, but on the other hand, it results in a vast ...
Franc Novak, Anton Biasizzo
doaj   +1 more source

Precision analysis for hardware acceleration of numerical algorithms

, 2012
The precision used in an algorithm affects the error and performance of individual computations, the memory usage, and the potential parallelism for a fixed hardware budget. However, when migrating an algorithm onto hardware, the potential improvements
Boland, David Peter, Boland, David Peter
core   +1 more source

Self‐Healing and Stretchable Synaptic Transistor

Advanced Functional Materials, EarlyView.
A self‐healing stretchable synaptic transistor (3S‐T) is realized using a p‐PVDF‐HFP‐DBP/PDMS‐MPU‐IU bilayer as gate insulator, where dipole‐dipole interaction enhances polarization to achieve a large memory window. Leveraging its neuronal biomimicry, the synaptic transistor demonstrates electrically compatibility with the biological brain. Furthermore,
Hyongsuk Choo, Sangyong Park, Yoonyi Jeong, Jaepyo Jang, Duhwan Seong, In Soo Kim, Myung‐Gil Kim, Mikyung Shin, Minah Suh, Donghee Son, Jin‐Hong Park   +10 more
wiley   +1 more source

Fine grain algorithm parallelization on a hybrid control-flow and dataflow processor

Journal of Big Data
The execution time of a high-performance computing algorithm is influenced by various factors, including the algorithm's scalability, the selected hardware for processing elements, and the communication speed between these elements. This study utilizes a
Nenad Korolija
doaj   +1 more source

BrainFrame: A node-level heterogeneous accelerator platform for neuron simulations

, 2017
Objective: The advent of High-Performance Computing (HPC) in recent years has led to its increasing use in brain study through computational models. The scale and complexity of such models are constantly increasing, leading to challenging computational ...
Al-Ars, Zaid, Chatzikonstantis, Georgios, De Zeeuw, Chris I., Kachris, Christoforos, Kukreja, Rahul, Rodopoulos, Dimitrios, Sidiropoulos, Harry, Smaragdos, Georgios, Soudris, Dimitrios, Sourdis, Ioannis, Strydis, Christos   +10 more
core   +1 more source

Dual‐Mode Magnetic Elastomer for On‐Demand Motion and Degradation

Advanced Functional Materials, EarlyView.
A dual‐mode magnetic elastomer is introduced, enabling DC field‐driven programmable actuation and AC field‐driven magnetothermal degradation. GHz‐range magnetic fields generate ultrafast heating of magnetic nanoparticles that activates cleavage of the silicone elastomer matrix.
Jieun Han, Hyun An, Min‐Ha Oh, Yu‐Lim Lee, Woojin Jeon, Kyung‐Sub Kim, Jae‐Hwan Lee, Seungmin Kang, Yoon‐Nam Kim, Ji‐Won Kang, Daewhan Kim, Min Sang Kwon, Sang‐Koog Kim, Seung‐Kyun Kang   +13 more
wiley   +1 more source

Hardware Acceleration for Deep Learning

Proceedings of the International Florida Artificial Intelligence Research Society Conference
Deep learning neural models require hardware acceleration. The current thirst for this acceleration is exceeding current capabilities and reality. At current trends, by 2045, one half of the world’s electricity will be consumed by training deep learning
David Bisant
doaj  

NIST torsion oscillator viscometer response: Performance on the LeRC active vibration isolation platform [PDF]

Critical point viscosity measurements are limited to their reduced temperature approach to T(sub c) in an Earth bound system, because of density gradients imposed by gravity.
Berg, Robert F., Grodsinsky, Carlos M.
core   +1 more source

The Hardware Accelerator SFDL/SCL.

Comput. Artif. Intell., 2012
This paper presents a new multiprocessor architecture for modelling and simulation of digital circuits. To speed up the simulation process a special static algorithm for dividing modelled circuit components into equivalent classes (before the simulation starts) has been designed. In components of one class events will never appear at the same time. The
Blatný, J., Bartoněk, D.
openaire   +1 more source

Optoelectrical Devices for Neural Interfacing: Engineering Integration, Stability, and Multimodal Sensing

Advanced Healthcare Materials, EarlyView.
Implantable optoelectrical devices are an effective resource for the modulation and monitoring of neural activity with high spatiotemporal resolution. This review discusses current challenges faced by these devices and outlines future perspectives for the development of next‐generation neural interfaces targeting chronic, multisite, and multimodal ...
Stella Aslanoglou, Barbara Spagnolo, Antonio Balena, Massimo De Vittorio, Ferruccio Pisanello   +4 more
wiley   +1 more source