Abstract
As the scope of artificial intelligence (AI) expands and the structure becomes more complex, the amount of data for inference and training has increased. In traditional computer architectures, the memory bandwidth limitations have intensified bottlenecks in AI systems, and processing-in-memory (PIM) architectures have been proposed to overcome this issue. PIM is an architecture that performs computations within memory, thereby reducing data movement between the CPU and memory. However, since PIM is difficult to optimize as a general-purpose architecture, it is essential to adopt an architecture suitable for the target application. While various simulators and emulators have been introduced for the design space exploration (DSE) of different PIM architectures, simulators are limited in debugging hardware operations, and emulators face challenges in flexibly modifying the system configuration, as emulators implement the entire architecture in hardware. Therefore, this paper introduces PIMCoSim, a comprehensive hardware–software co-simulator for the DSE of DRAM-PIM systems. This co-simulator partially emulates simplified hardware-implemented processing elements (PEs) and integrates software models for memory operations, facilitating the DSE of PIM systems. To validate PIMCoSim, we analyzed results for different computational workloads by varying PIM structures and operational policies, demonstrating the efficiency of DRAM-PIM systems. The co-simulation approach in PIMCoSim aims to contribute to analyzing DRAM-PIM configurations and adopting optimized structures.
Published Version
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