Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Gangotree Chakma"'
Autor:
Chris Hobbs, Martin Rodgers, Wilkie Olin-Ammentorp, Joseph E. Van Nostrand, Nathaniel C. Cady, Garrett S. Rose, Gangotree Chakma, Karsten Beckmann, Sherif Amer
Publikováno v:
ACM Journal on Emerging Technologies in Computing Systems. 16:1-18
Resistive Random Access Memory (ReRAM), a form of non-volatile memory, has been proposed as a Flash memory replacement. In addition, novel circuit architectures have been proposed that rely on newly discovered or predicted behavior of ReRAM. One such
Autor:
Thomas E. Potok, Robert M. Patton, Federico M. Spedalieri, Garrett S. Rose, Ke-Thia Yao, Catherine D. Schuman, Jeremy Liu, Steven R. Young, Gangotree Chakma
Publikováno v:
ACM Journal on Emerging Technologies in Computing Systems. 14:1-21
Current deep learning approaches have been very successful using convolutional neural networks trained on large graphical-processing-unit-based computers. Three limitations of this approach are that (1) they are based on a simple layered network topo
Autor:
Gangotree Chakma, Austin Wyer, Ryan J. Weiss, Musabbir Adnan, Garrett S. Rose, Catherine D. Schuman
Publikováno v:
IEEE Journal on Emerging and Selected Topics in Circuits and Systems. 8:125-136
Neuromorphic computing is non-von Neumann computer architecture for the post Moore’s law era of computing. Since a main focus of the post Moore’s law era is energy-efficient computing with fewer resources and less area, neuromorphic computing con
Publikováno v:
ICECS
Several researchers have proposed that random noise in highly non-linear biological systems helps with learning and information processing. Neuromorphic systems could potentially harness the computational power of such biological systems by utilizing
Autor:
Gangotree Chakma, Shaan Awasthi
Publikováno v:
IEEE BigData
Memory and Central Processing Units (CPU) are the primary computing resources for any circuit simulation job. Speed, efficiency and performance of these jobs depends on how the resources in the server farm are leveraged and optimized. But depending o
Autor:
Nicholas D. Skuda, Mark Edward Dean, Gangotree Chakma, Garrett S. Rose, Catherine D. Schuman, James S. Plank
Publikováno v:
ACM Great Lakes Symposium on VLSI
Resource constrained devices are the building blocks of the internet of things (IoT) era. Since the idea behind IoT is to develop an interconnected environment where the devices are tiny enough to operate with limited resources, several control syste
Publikováno v:
ISCAS
Neuromorphic computing systems are alternatives to conventional microprocessors, often built from unconventional hardware. Designing and evaluating these systems requires multiple levels of simulation, from the device level to the circuit level to th
Autor:
James S. Plank, Nouamane Laanait, Austin Wyer, Catherine D. Schuman, Grant Bruer, Garrett S. Rose, Gangotree Chakma
Publikováno v:
NANOCOM
Neuromorphic computing is a promising post-Moore's law era technology. A wide variety of neuromorphic computer (NC) architectures have emerged in recent years, ranging from traditional fully digital CMOS to nanoscale implementations with novel, beyon
Publikováno v:
MWSCAS
In this paper we present circuit techniques to optimize analog neurons specifically for operation in memristive neuromorphic systems. Since the peripheral circuits and control signals of the system are digital in nature, we take a mixed-signal circui
Publikováno v:
MWSCAS
In this paper we present a memristive neuromorphic system for higher power and area efficiency. The system is based on a mixed signal approach considering the digital nature of the peripheral and control logics and the integration being analog. So, t