Code Generation: A Strategy for Neural Network Simulators
Code Generation: A Strategy for Neural Network Simulators
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DOI：
10.1007/s12021-010-9082-x
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发表时间：
2010-10-01
期刊：
影响因子：
3
通讯作者：
Goodman, Dan F. M.
中科院分区：
文献类型：
--
作者：
Goodman, Dan F. M.
我们演示了一种用于设计神经网络模拟软件的技术，即运行时代码生成。该技术可用于为用户提供完全的灵活性，以高级方式指定其模拟的数学模型，以及用低级语言（例如 C++）编写的代码的速度。它还可以用于仅编写一次代码，但针对不同的硬件平台，包括廉价的高性能图形处理单元（GPU）。代码生成可以自然地与计算机代数系统结合，以进一步简化和优化生成的代码。该技术非常通用，可以应用于任何模拟包。我们用“Brian”模拟器 (http://www.briansimulator.org) 来演示它。
We demonstrate a technique for the design of neural network simulation software, runtime code generation. This technique can be used to give the user complete flexibility in specifying the mathematical model for their simulation in a high level way, along with the speed of code written in a low level language such as C++. It can also be used to write code only once but target different hardware platforms, including inexpensive high performance graphics processing units (GPUs). Code generation can be naturally combined with computer algebra systems to provide further simplification and optimisation of the generated code. The technique is quite general and could be applied to any simulation package. We demonstrate it with the 'Brian' simulator (http://www.briansimulator.org).