# SARDIM: High-Speed Near-Memory Processing Architecture for Synthetic Aperture Radar Imaging
## 1 Introduction
Addressing these issues can lead to more sustainable and cost-effective SAR imaging, aligning with the broader goal of improving both performance and resource utilization in SAR technology. Figure 1 illustrates the RDA 2D-FFT operation within the roofline model to demonstrate that it is memory-bound. The roofline model serves as a framework for analyzing performance constraints in computer systems, focusing on the balance between memory bandwidth and operations per second, and particularly emphasizing floating-point operations [24]. It is worth noting that the approach we used to apply the FFT within the roofline model is similar to the methodology presented in [25]. However, while [25] utilized a GPU platform for their analysis, our experiments were conducted on a CPU platform, specifically chosen to align with the DIMM-based memory configuration of our system. Despite the difference in hardware platforms, our results are consistent with those of [25], further validating our methodology. To construct the roofline model, we used a PyTorch profiler to assess the 2D-FFT performance. The CPU used in the experiments was an Intel(R) Core(TM) i7-10700K. It features two memory channels, each equipped with DDR4-2933 dual in-line memory modules (DIMMs), providing a theoretical peak floating-point performance of 486.4 GFLOPs/s and a peak memory bandwidth of 45.8 GB/s [26]. The observed performance of the 8192 \(\times\) 8192 2D-FFT was 55.2 GFLOPs/s, representing only 11% of the peak floating-point performance. Figure 1 shows that the 2D-FFT is located in the memory-bound area of the roofline model. The numerous memory requests and bottlenecks associated with the 2D-FFT, which is a memory-constrained operation, can be mitigated through near-memory processing (NMP), a technique that has gained attention in recent research. Modern computer systems have limitations in terms of improving performance owing to memory bandwidth constraints and delays caused by data movement. NMP is one of the methods proposed for overcoming these limitations. NMP is a technology that minimizes unnecessary data movement, improves performance by processing operations in a memory area close to the data, and can effectively solve memory-bound challenges. Although various NMP-related studies primarily designed to accelerate artificial intelligence (AI) computations, such as vector addition and matrix multiplication, exist [27; 28; 29; 30; 31], no studies have focused on accelerating FFT for SAR image generation. Considering the critical role of FFT in SAR image generation and its inherent memory-bound nature, applying NMP to algorithms for radar signal processing holds the potential for significant improvements in execution time and energy efficiency. Therefore, exploring the application of NMP in SAR image generation to achieve these improvements represents a promising direction for future research. In this study, we propose a synthetic aperture radar dual in-line memory module (SARDIMM), which effectively improves the performance of the RDA by applying rank-level parallel NMP to FFT, IFFT, and matched filter operations, which are core processes in the RDA. To the best of our knowledge, this is the first instance where SAR image generation has been implemented using NMP. Our research demonstrates that by applying NMP to SAR applications, we can achieve significant gains in both speed and power. We believe that these contributions are valuable in advancing the current state of SAR imaging technology. SARDIMM achieves a significant reduction in unnecessary data movement, improved execution time, and reduced power consumption by executing specific RDA operations in NMP modules located near memory. Because the NMP module is located between the memory and the memory controller, SARDIM uses a commodity dynamic random-access memory (DRAM) chip without additional modifications. The NMP module selectively supports a combination of FFT, IFFT, and matched filter operations to perform the RDA range and azimuth compression.