In-Memory Associative Processors: Tutorial, Potential, and Challenges
In-Memory Associative Processors: Tutorial, Potential, and Challenges
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内存关联处理器：教程、潜力和挑战
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发表时间：
2022
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通讯作者：
F. Kurdahi
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作者：
M. Fouda;Hasan Erdem Yantır;A. Eltawil;F. Kurdahi
内存计算是一种新兴的计算范式，它克服了现有冯诺依曼计算体系结构的局限性，如内存墙瓶颈。在这种范例中，直接对存储在存储器中的数据执行计算，这大大减少了计算期间的存储器-处理器通信。因此，可以实现显著的加速和节能，特别是对于数据密集型应用程序。联想处理器（AP）是在70年代提出的，最近由于高密度存储器的出现而复活。在本教程中，我们概述了AP的功能和最新趋势，以及使用不同技术实现的每个内容可寻址内存。最后总结了AP操作和运行时复杂度。我们还解释和探讨了可能的应用程序，可以受益于AP。最后，AP的局限性，挑战和未来的发展方向进行了讨论。
In-memory computing is an emerging computing paradigm that overcomes the limitations of exiting Von-Neumann computing architectures such as the memory-wall bottleneck. In such paradigm, the computations are performed directly on the data stored in the memory, which highly reduces the memory-processor communications during computation. Hence, significant speedup and energy savings could be achieved especially with data-intensive applications. Associative processors (APs) were proposed in the seventies and recently were revived thanks to the high-density memories. In this tutorial brief, we overview the functionalities and recent trends of APs in addition to the implementation of each content-addressable memory with different technologies. The AP operations and runtime complexity are also summarized. We also explain and explore the possible applications that can benefit from APs. Finally, the AP limitations, challenges, and future directions are discussed.