In-memory computing seeks to minimize data movement and alleviate the memory wall by computing in-situ, in the same place that the data is located. One of the key emerging technologies that promises to enable such computing-in-memory is spin-transfer torque magnetic tunnel junction (STT-MTJ). This paper proposes AM4, a combined STT-MTJ-based Content Addressable Memory (CAM), Ternary CAM (TCAM), approximate matching (similarity search) CAM (ACAM), and in-memory Associative Processor (AP) design, inspired by the recently announced Samsung MRAM crossbar. We demonstrate and evaluate the performance and energy-efficiency of the AM4-based AP using a variety of data intensive workloads. We show that an AM4-based AP outperforms state-of-the-art solutions both in performance (with the average speedup of about 10 ×) and energy-efficiency (by about 60 × on average).
|Number of pages||14|
|Journal||IEEE Journal on Emerging and Selected Topics in Circuits and Systems|
|State||Published - 1 Mar 2023|
Bibliographical notePublisher Copyright:
© 2011 IEEE.
- Non-von Neumann computer architecture
- associative memories
- associative processor
- double-barrier MTJ
- emerging memories