Asanović K, Beck J, Feldman J, Morgan N, Wawrzynek J
University of California, Berkeley.
Int J Neural Syst. 1993 Dec;4(4):317-26. doi: 10.1142/s0129065793000250.
This paper describes an effort at UC Berkeley and the International Computer Science Institute to develop a supercomputer for artificial neural network applications. Our perspective has been strongly influenced by earlier experiences with the construction and use of a simpler machine. In particular, we have observed Amdahl's Law in action in our designs and those of others. These observations inspire attention to many factors beyond fast multiply-accumulate arithmetic. We describe a number of these factors along with rough expressions for their influence and then give the applications targets, machine goals and the system architecture for the machine we are currently designing.
本文介绍了加州大学伯克利分校和国际计算机科学研究所为开发用于人工神经网络应用的超级计算机所做的努力。我们的观点深受早期构建和使用一台更简单机器的经验的强烈影响。特别是，我们在自己的设计以及其他人的设计中观察到了阿姆达尔定律的实际作用。这些观察促使我们关注快速乘法累加运算之外的许多因素。我们描述了其中一些因素及其影响的粗略表达式，然后给出了应用目标、机器目标以及我们目前正在设计的机器的系统架构。
