Exploring the DIMM PIM Architecture for Accelerating Time Series Analysis

Time series analysis (TSA) is an important technique for extracting information from domain data. TSA is memory-bound on conventional platforms due to excessive off-chip data movements between processing units and the main memory of the system. Processing in memory (PIM) is a paradigm that alleviates the bottleneck of memory access for data-intensive applications by enabling computation to be performed directly within memory. In this paper, we first perform profiling to characterize TSA on conventional CPUs. Then, we implement TSA on real-world commercial DRAM Dual-Inline Memory Module (DIMM) PIM hardware UPMEM and identify computation as the primary bottleneck on PIM. Finally, we evaluate the impact of enhancing the computational capability of current DIMM PIM hardware on accelerating TSA. Overall, our work provides insights for designing the optimized DIMM PIM architecture for high-performance and efficient time series analysis.