MUMBAI, India, Aug. 10 -- Intellectual Property India has published a patent application (202648090289 A) filed by Google LLC on July 24, 2026, for Exploiting Data Sparsity At A Machine-Learning Hardware Accelerator.
Inventors include Ayupov, Andrey; and Gupta, Suyog.
The application for the patent was published on July 31, 2026, under issue no. 31/2026.
Abstract: EXPLOITING DATA SPARSITY AT A MACHINE-LEARNING HARDWARE ACCELERATOR Methods and systems, including computer-readable media, are described for exploiting data sparsity during computations for a neural network implemented on a hardware accelerator. Using a system controller, a set of compressed sparse parameters is derived from a parameter tensor and a mapping vector is generated based on the set of compressed sparse parameters. When the system(s) processes an opcode in an instruction indicating sparsity of the parameter tensor, an input vector is obtained from a first memory of the hardware accelerator and the compressed sparse parameters and the mapping vector are retrieved from a second memory of the hardware accelerator. The input vector is processed through a layer of the neural network using the mapping vector and the set of compressed sparse parameters. FIG. 6
Disclaimer: Curated by HT Syndication.
