Cornell University

About: Cornell University is a education organization based out in Ithaca, New York, United States. It is known for research contribution in the topics: Population & Gene. The organization has 102246 authors who have published 235546 publications receiving 12283673 citations. The organization is also known as: Cornell & CUI.

TrueNorth: Design and Tool Flow of a 65 mW 1 Million Neuron Programmable Neurosynaptic Chip

Abstract: The new era of cognitive computing brings forth the grand challenge of developing systems capable of processing massive amounts of noisy multisensory data. This type of intelligent computing poses a set of constraints, including real-time operation, low-power consumption and scalability, which require a radical departure from conventional system design. Brain-inspired architectures offer tremendous promise in this area. To this end, we developed TrueNorth, a 65 mW real-time neurosynaptic processor that implements a non-von Neumann, low-power, highly-parallel, scalable, and defect-tolerant architecture. With 4096 neurosynaptic cores, the TrueNorth chip contains 1 million digital neurons and 256 million synapses tightly interconnected by an event-driven routing infrastructure. The fully digital 5.4 billion transistor implementation leverages existing CMOS scaling trends, while ensuring one-to-one correspondence between hardware and software. With such aggressive design metrics and the TrueNorth architecture breaking path with prevailing architectures, it is clear that conventional computer-aided design (CAD) tools could not be used for the design. As a result, we developed a novel design methodology that includes mixed asynchronous–synchronous circuits and a complete tool flow for building an event-driven, low-power neurosynaptic chip. The TrueNorth chip is fully configurable in terms of connectivity and neural parameters to allow custom configurations for a wide range of cognitive and sensory perception applications. To reduce the system’s communication energy, we have adapted existing application-agnostic very large-scale integration CAD placement tools for mapping logical neural networks to the physical neurosynaptic core locations on the TrueNorth chips. With that, we have successfully demonstrated the use of TrueNorth-based systems in multiple applications, including visual object recognition, with higher performance and orders of magnitude lower power consumption than the same algorithms run on von Neumann architectures. The TrueNorth chip and its tool flow serve as building blocks for future cognitive systems, and give designers an opportunity to develop novel brain-inspired architectures and systems based on the knowledge obtained from this paper.

Making Use of Difference: Diversity, Debate, and Decision Comprehensiveness in Top Management Teams

Abstract: This study examined how top management team diversity variables and debate interacted to influence two measures of company financial performance. Further, it assessed the degree to which decision c...

On the convergence of interior-reflective Newton methods for nonlinear minimization subject to bounds

Abstract: We consider a new algorithm, an interior-reflective Newton approach, for the problem of minimizing a smooth nonlinear function of many variables, subject to upper and/or lower bounds on some of the variables. This approach generatesstrictly feasible iterates by using a new affine scaling transformation and following piecewise linear paths (reflection paths). The interior-reflective approach does not require identification of an "activity set". In this paper we establish that the interior-reflective Newton approach is globally and quadratically convergent. Moreover, we develop a specific example of interior-reflective Newton methods which can be used for large-scale and sparse problems.

Value of Echocardiographic Measurement of Left Ventricular Mass in Predicting Cardiovascular Morbid Events in Hypertensive Men

Abstract: To assess whether echocardiographic and electrocardiographic detection of left ventricular hypertrophy could predict cardiovascular morbid events in patients with uncomplicated essential hypertension, we followed 140 men for a mean of 4.8 years. Initial echocardiographic measurements of left ventricular mass were normal (less than 125 g/m2 body surface area) in 111 patients and revealed hypertrophy in 29 patients. Morbid events occurred in more patients with hypertrophy on echocardiography (7 of 29, 4.6/100 patient-years) than with normal ventricular mass (7 of 111, 1.4/100 patient-years; p less than 0.01). Electrocardiography showed hypertrophy in too few patients to be of predictive value. Multiple logistic regression analysis showed that left ventricular mass index had the highest independent relative risk for future events and that systolic and diastolic pressures and age had slightly lower relative risks. In men with mild uncomplicated hypertension, left ventricular hypertrophy detected by echocardiography identifies patients at high risk for cardiovascular morbid events and is a significant risk factor for future morbid events independent of age, blood pressure, or resting ventricular function.