MUMBAI, India, Aug. 17 -- Intellectual Property India has published a patent application (202617084011 A) filed by Advanced Micro Devices, Inc. on July 08, 2026, for Systems And Methods To Accelerate Neural Network Computations In Heterogenous Computing Systems.
Inventors include Dash, Eashan; Ramachandran, Arun Coimbatore; Ramasamy, Chandra Kumar; Nagaraja, Ganesh Prasad; Madineni, Phani Shankar; and Raghavendra, Prakash Sathyanath.
The application for the patent was published on August 14, 2026, under issue no. 33/2026.
Abstract: Systems, methods, and apparatus for partial tensor correction are disclosed. During quantization, weight tensors can be corrected for quantization errors in order to increase accuracy that is otherwise degraded as a result of quantization. To correct errors, the weight tensor is partially corrected using a data-free, non-iterative, per- input channel level technique to achieve accuracy improvement while using lower precision. Further, sensitive channels prone to accuracy degradation due to quantization are identified. Based on this identification, parts of weight tensor is retained for CPU computation and remaining parts of the weight tensor are offloaded for accelerator computation. The proposed partial tensor retention scheme achieves efficient heterogenous DNN computations with improved performance and accuracy on heterogenous systems. Furthermore, combining the partial tensor correction and partial tensor retention techniques allows for achieving improved performance and accuracy in a heterogenous computing environment while using low precision computations.
Disclaimer: Curated by HT Syndication.
