The trend of CIM
Computing in Memory (CIM) is a trend in computer architecture aimed at addressing the growing gap between data processing speed and transfer speed in traditional architectures. In traditional architectures, data must be transferred between the CPU and memory, which can result in significant delays and energy consumption, especially as data sizes increase.
CIM can overcome these limitations mainly by executing computations directly within the memory units themselves, thereby reducing data movement and lowering power consumption. This approach can greatly accelerate certain types of computations, especially those involving large datasets or repetitive operations.
CIM enables faster and more energy-efficient computations on large datasets, revolutionizing various applications such as AI, data analytics, and scientific simulations. As the demand for high-performance computing continues to grow, CIM is expected to play an increasingly important role in future computer architectures.
Testing algorithm behaviors for CIM
Taking March C- of 8T-SRAM based CIM as an example, after the “r0w1” operation in the upward and downward rows, a behavior has been added. This behavior involves performing a NAND operation between the data of i cell and the data of i+1 cell. The NAND operation can be replaced with the following behaviors:
Behavior One: OR, NOR, NAND, XOR, XNOR, XAND, Multiplication, Addition.
Behavior Two:
How to generate specific algorithms dedicated to CIM?
In traditional algorithm behaviors, the values of read and write must be the same, or it will lead to comparison errors. By using iSTART-TEK’s User-Defined Algorithms (UDA) to develop CIM-dedicated algorithms, users can determine the values of read and write, thereby breaking the limit of traditional algorithms.
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