论文标题
内存的协会处理器：教程，潜在和挑战
In-memory Associative Processors: Tutorial, Potential, and Challenges
论文作者
论文摘要
内存计算是一种新兴的计算范式，它克服了退出Von-Neumann计算体系结构（例如内存壁瓶颈）的局限性。在这种范式中，计算直接在存储在存储器中的数据上执行，这在计算过程中高度降低了内存处理器通信。因此，尤其是在数据密集型应用程序中，可以实现大量的加速和节能。七十年代提出了协会处理器（AP），并由于高密度的记忆而恢复了。在本教程简介中，我们概述了除了使用不同技术实施每个内容 - 可压制的内存外，APS的最新趋势和趋势。还总结了AP操作和运行时复杂性。我们还解释并探索可能受益于AP的可能应用。最后，讨论了AP的限制，挑战和未来的方向。
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.
