Systolic Array Matrix Multiplier: The Heart of AI Accelerators

What is a Systolic Array?

A systolic array is a specialized hardware architecture designed to perform matrix operations efficiently. It consists of an array of processing elements (PEs) arranged in a grid, where each PE performs a simple computation and communicates with its neighbors via data channels.

The key feature of a systolic array is the pipelined nature of the computations: as data flows through the array, each PE performs a single operation per clock cycle, contributing to the overall matrix multiplication.

How Does It Work?

In a systolic array for matrix multiplication, one matrix is fed into the array row by row, while another is fed column by column. Each PE in the array performs a multiply-accumulate operation (MAC) on its input values from neighboring PEs.

As the data flows through the array, a diagonal wavefront of active PEs sweeps across the grid, computing partial results that are then passed to subsequent PEs for further processing until the final result is obtained.

Why It Matters

Systolic arrays are crucial in modern AI accelerators because they offer high throughput and low latency for matrix operations, which are fundamental in deep learning algorithms.

By leveraging parallel processing and pipelining, systolic arrays can handle large matrices efficiently, making them ideal for training and inference tasks in artificial intelligence.

Real-World Applications

Systolic arrays are used in tensor cores of GPUs and TPU matrix units (MXUs) to accelerate the performance of neural network computations.

They enable rapid processing of large datasets, making them indispensable for applications such as image recognition, natural language processing, and autonomous driving.

Frequently asked questions

Try it live

Everything above runs in your browser — open Systolic Array Matrix Multiplier and change the parameters while it is running. Nothing is installed, nothing is uploaded, the whole model lives in one tab.