Refereed International Conference Poster

Approximation-based Inter-PE Communication-free Image Filtering for Commodity PIM [abstract]
Chan Lee, Shinnung Jeong, Heelim Choi, Jaeho Lee, Haeeun Jeong, Hoyun Youm, Ju Min Lee, and Hanjun Kim
Proceedings of the 62th Annual Design Automation Conference 2025 - (Poster) (DAC), June 2025.

With the increasing size of images and the widespread use of image filtering like photo enhancement, noise reduction and edge detection, rapid handling extensive amounts of pixel data becomes required for image processing tasks. However, the limited computing resources and memory bandwidth pose constraints on the rapid image filtering. Processing-in-Memory (PIM) architectures can solve the issue by integrating parallel processing elements (PEs) within memory and minimizing data movement, but existing PIM-based image filtering approaches require data sharing between the PEs causing huge communication overheads due to the lack of direct inter-PE communication support in commodity PIM systems. To address this limitation, we propose a new approximation-based inter-PE communication-free image filtering scheme for commodity PIM systems called ApplePIM. By approximating partitioned image boundaries in the filtering process, ApplePIM efficiently removes inter-PE communication across multiple PEs in a commodity PIM. Furthermore, ApplePIM analyzes error sensitivity of the image filter, and dynamically determines its approximation method depending on the sensitivity. If the image filter is too sensitive on all the approximation methods, ApplePIM conservatively duplicates the boundaries of image partitions, thus avoiding inter-PE communication at a little cost of additional memory usage.