FIR Systolic Arrays Mapping A FIR systolic array is a specialized architecture used in digital signal processing (DSP) systems to perform systolic proces...
A FIR systolic array is a specialized architecture used in digital signal processing (DSP) systems to perform systolic processing. Systolic processing involves a series of interconnected systolic blocks that perform convolution operations on data received sequentially along the array.
Systolic arrays offer several advantages over traditional linear architectures:
Parallelism: Systolic blocks can operate in parallel, significantly reducing the processing time required for complex operations.
Data locality: Data is processed in small chunks, minimizing memory access overhead.
Reduced latency: systolic arrays can achieve lower latency compared to linear architectures, as they eliminate the need for data buffering.
Here's how the FIR systolic array mapping works:
Mapping: A data buffer containing the input data is first organized into a specific order within the systolic array.
Placement: Each systolic block in the array is assigned a specific location in the buffer based on its index.
Data transfer: Data is transferred from the buffer to the systolic block through dedicated communication channels within the array.
Convolution: Each systolic block applies the FIR convolution operation to its assigned data portion.
Output generation: The output of the systolic block is then passed to the next block in the chain.
Data transfer back to the main memory: Finally, the processed output is transferred back to the main memory for further processing or output.
An example of FIR systolic array mapping:
Consider a 32-point systolic array with systolic blocks of size 4. The input data is first loaded into the array's buffer. Each block processes 4 consecutive samples, and the outputs are then merged and outputted.
Benefits of FIR systolic array mapping include:
High performance: Can achieve significantly lower latency compared to linear architectures.
Reduced memory requirements: Data is processed in small chunks, minimizing memory access overhead.
Parallelism: Systolic blocks can operate in parallel, further improving performance.
Applications of FIR systolic arrays include:
Digital signal processing (DSP): For tasks like image processing, filtering, and compression.
Communications: For data aggregation and transmission.
Medical imaging: In medical imaging systems for real-time processing.
By understanding and implementing FIR systolic array mapping, engineers can achieve significant performance improvements and design efficient computational systems for various applications