Computational Memory : The computing fabric of the future

在硬件中实现计算的传统方法是设计一个生成所需结果的算法，然后使用组合逻辑实现该算法。另一种在硬件中实现计算的方法是机械记忆，即预先计算所有结果并将它们存储在内存中，这种方法我们称为计算内存。我们的前提是，随着技术向更高密度扩展，计算内存具有特别有用的特性，但可靠性较低，性能变异性较高。存储器是非常规则的，因此非常密集，易于测试，并且比逻辑更平稳地耗电。原则上，可以使用纠错码和/或错误检测和重新计算来系统地实现对存储器和互连的容错，从而提供了一种途径来解决超大规模技术衬底中的可靠性和性能差异。这样的计算内存块是完全可组合的，使得容错设计更容易处理，错误覆盖率要高得多。然而，即使在我们可以支配的高密度情况下，计算内存的幼稚实现对指数级内存的要求也让人对其实用性产生了质疑。拟议的研究将表明，通过组合使用替代数字系统、编码、缓存和体系结构技术，可以克服这种可伸缩性问题。如果这项工作取得成功，基于计算内存的可编程结构可能会成为纳米技术时代的标准计算框架。有朝一日，这可能会使廉价的“计算棒”能够提供便携式计算能力，以及今天的外形--S闪存--的永久存储。

The traditional way to realize computation in hardware is to devise an algorithm that generates the desired result and then implement that algorithm using combinational logic. Another way to realize computation in hardware is rote memorization, i.e., precompute all the results and store them in memory, a method we call Computational Memory. Our premise is that Computational Memory has properties that are particularly useful as technologies scale to higher densities, but lower reliability and higher performance variability. Memories are very regular and thus very dense, easy to test, and dissipate power much more smoothly than logic. Fault-tolerance on memories and interconnects can, in principle, be systematically implemented using error-correcting codes and/or error detection and recomputation, providing an avenue to address both reliability and performance variability in ultrascaled technology substrates. Such computational memory blocks are cleanly composable, making fault-tolerant designs more tractable with much higher fault coverage. However, even with the high densities that are at our disposal, the exponential memory requirements of a naive implementation of Computational Memory calls into question its practicality. The proposed research will show that this scalability problem can be overcome through the combined use of alternative number systems, coding, caching and architectural techniques. If this work is successful, programmable fabrics based on Computational Memory might emerge as a standard computing framework for the nanotechnology era. This might someday enable inexpensive "computing sticks" that provide portable computing power, along with persistent storage in the form-factor of today?s flash memory.