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DARPA SOAP Seeks Innovation: Scalable On-Array Processing to Revolutionize Signal Processing

The U.S. Defense Advanced Research Projects Agency (DARPA), renowned for fostering groundbreaking technologies, has issued a new challenge: the Scalable On-Array Processing (SOAP) program. This initiative aims to revolutionize the way we handle digital signal processing, particularly for large-scale applications like phased arrays.

The Challenge: Breaking Through Processing Barriers

Digital signal processing (DSP) is the backbone of numerous technologies, from radar and communication systems to medical imaging. However, traditional DSP methods rely on large matrix operations that become increasingly cumbersome and time-consuming as data volumes grow. This poses a significant challenge for applications like phased arrays, which require real-time processing of massive amounts of data. This exponential growth in processing time renders conventional DSP methods impractical for large-scale phased arrays.

For example, modern phased arrays with over 1000 elements and instantaneous bandwidths (IBWs) of 1 GHz may require real-time numerical inversion of matrices as large as 1000 x 1000, with data rates exceeding 1 Tbps between the array front end and intermediate processor stages. These digital bottlenecks severely limit the number of independent elements and IBWs achievable in today’s digital array architectures. These bottlenecks increase with both the number of elements in the array and the IBW of each element.

There are two primary types of digital bottlenecks: processing bottlenecks and data movement bottlenecks. Processing bottlenecks arise from the computational complexity of array processing algorithms, which scale exponentially with the number of elements in the array. Data movement bottlenecks occur when array data must be processed on a centralized back-end processor, requiring large amounts of power and creating limitations on data movement capacity.

The SOAP Solution: Co-Designing Hardware and Software

DARPA’s SOAP program proposes a paradigm shift: co-designing scalable algorithms with specialized hardware architectures. This two-pronged approach aims to break the matrix operation bottleneck and achieve efficient, high-performance DSP for large-scale applications.

  • Algorithm Innovation: Beyond Traditional DSP Techniques

SOAP encourages researchers to explore novel algorithms from diverse fields like machine learning, high-performance computing, and even scientific computing. These algorithms should be adept at exploiting the inherent parallelism of hardware architectures for efficient on-array processing.

  • Hardware Optimization: Customizing the Processing Engine

Instead of relying on general-purpose processors, SOAP seeks the development of Application-Specific Integrated Circuits (ASICs) or Field-Programmable Gate Arrays (FPGAs) tailored specifically to run the chosen algorithms. These custom architectures can be optimized for specific mathematical operations and data flow, leading to significant performance gains.

By leveraging recent research in interconnect technologies and distributed processing, SOAP aims to enable wideband digital arrays that can support high beam counts and multifunction operation with low latency.

Technical Considerations for Scalability

To achieve true scalability, the SOAP program emphasizes several key technical aspects:

  • Dataflow Architectures: Designing efficient dataflow architectures within the hardware is crucial for minimizing data movement and maximizing processing throughput. Techniques like systolic arrays and pipelined processing can be explored.
  • Algorithm Parallelization: The chosen algorithms need to be highly parallelizable, meaning they can be broken down into independent tasks that can be executed simultaneously on multiple processing units within the custom hardware.
  • Low-Precision Computing: Exploring techniques like low-precision arithmetic (e.g., fixed-point or reduced-width floating-point) can offer a compelling trade-off between processing speed and accuracy, especially for applications where exact precision is not essential.

The Target Application: Next-Generation Phased Arrays

The primary application of the SOAP program is in elemental digital phased arrays.  Phased arrays are antenna systems that electronically steer a beam of radio waves in a particular direction by manipulating the phases of the signals emitted from each antenna element. These arrays play a vital role in radar, communication, and electronic warfare systems. By enabling scalable on-array processing, SOAP aims to revolutionize phased array technology:

    • Arbitrary Size and Bandwidth: SOAP envisions phased arrays that can be scaled to much larger sizes (potentially thousands of elements) and handle wider ranges of frequencies compared to current limitations. This opens doors for advanced radar systems with finer resolution and wider coverage areas.
    • Real-Time Performance: Scalable on-array processing promises to significantly reduce processing times, enabling real-time operation for even the largest and most complex phased arrays. This is critical for applications like high-performance radars and electronic countermeasures.

The Call for Innovation

DARPA is seeking a collaborative effort from researchers and companies with expertise in both algorithm development and hardware design. Ideal candidates will possess:

  • Algorithm Design Expertise: The ability to develop innovative, highly parallelizable algorithms for on-array processing, potentially leveraging techniques from non-traditional DSP disciplines.
  • Hardware Architecture Knowledge: Experience in designing custom hardware architectures (ASICs or FPGAs) optimized for the chosen algorithms and dataflow requirements.

The Road Ahead: A More Efficient Future for Signal Processing

The SOAP program holds immense potential to revolutionize the field of digital signal processing. By fostering collaboration between algorithm developers and hardware architects, SOAP could pave the way for a new era of efficient and scalable processing solutions. The goal is to revolutionize phased array processing and design, enabling new applications and capabilities that were not possible with traditional array architectures.

This has far-reaching implications not only for military applications but also for advancements in communication, radar, and other civilian technologies that rely heavily on DSP. The success of SOAP could unlock a future where processing power scales seamlessly with data demands, leading to significant performance gains across diverse fields.

About Rajesh Uppal

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