An open architecture for the massively parallel emulation of the Drosophila brain on multiple GPUs
© Givon and Lazar; licensee BioMed Central Ltd. 2012
Published: 16 July 2012
The fruit fly Drosophila melanogaster is an exceedingly useful model organism for studying the causal links between neural circuits and behavior due to the numerical tractability of its brain and its powerful neurogenetic toolkit. Recent progress made in identifying the connectome of the fruit fly [1, 2] and in characterizing the input and output functions of its sensory neural circuits  raise the possibility of creating and emulating a functional model of the entire fly brain using the increasingly powerful commodity parallel computing technology available to computational neuroscientists. To this end, we have developed an open software architecture for emulating neural circuit modules in the fly brain and their responses to recorded or simulated input stimuli on multiple Graphics Processing Units (GPUs). A key feature of this architecture is its support for integrating instances of different neural circuit models developed by independent researchers by requiring that the models’ implementations provide interoperable interfaces that adhere to the specification prescribed by the architecture.
We implemented key elements of the Neurokernel software using the Python programming language and the PyCUDA interface to NVIDIA’s CUDA GPU programming environment  to avail ourselves of the increasingly powerful ecosystem of scientific computing Python software and make the architecture accessible to other researchers in the neuroscience community.
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