Translating network models to parallel hardware in NEURON
نویسندگان
چکیده
منابع مشابه
Translating network models to parallel hardware in NEURON.
The increasing complexity of network models poses a growing computational burden. At the same time, computational neuroscientists are finding it easier to access parallel hardware, such as multiprocessor personal computers, workstation clusters, and massively parallel supercomputers. The practical question is how to move a working network model from a single processor to parallel hardware. Here...
متن کاملTranslating HOL functions to hardware
Delivering error-free products is still a major challenge for hardware and software engineers. Due to the increasingly growing complexity of computing systems, there is a demand for higher levels of automation in formal verification. This dissertation proposes an approach to generate formally verified circuits automatically. The main outcome of our project is a compiler implemented on top of th...
متن کاملHardware computation of conductance-based neuron models
We review di4erent applications of silicon conductance-based neuron models implemented on analog circuits. At the single-cell level, we describe a circuit in which conductances are programmed to simulate various Hodgkin–Huxley type models; integrated in a hardware/software system, they provide a simulation tool; an illustrative example is the simulation of bursting neurons of the thalamus. At t...
متن کاملa frame semantic approach to the study of translating cultural scripts in salingers franny and zooey
the frame semantic theory is a nascent approach in the area of translation studies which goes beyond the linguistic barriers and helps us to incorporate cognitive and cultural factors to the study of translation. based on rojos analytical model (2002b), which centered in the frames or knowledge structures activated in the text, the present research explores the various translation problems that...
15 صفحه اولParallel Hybrid Network Traffic Models
Fluid-based network traffic models are attractive due to their execution efficiency. They run much faster than the corresponding discrete-event packet-oriented simulation, especially when we study the aggregate traffic behavior of large-scale network scenarios. The efficiency, however, comes at a cost—fluid modeling does not include packet-level details. The ability to accurately capture the in...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Neuroscience Methods
سال: 2008
ISSN: 0165-0270
DOI: 10.1016/j.jneumeth.2007.09.010