Image rendering methods, apparatus, electronic devices and storage media

By forcibly modifying clipping parameters and reducing the rendering area in GPU software modeling, the problem of wasted time and manpower costs in GPU verification is solved, and verification efficiency is improved.

CN119784913BActive Publication Date: 2026-05-26MOORE THREADS TECHNOLOGY (SHANGHAI) CO LTD
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
MOORE THREADS TECHNOLOGY (SHANGHAI) CO LTD
Filing Date
2024-12-12
Publication Date
2026-05-26

AI Technical Summary

Technical Problem

In the process of GPU software modeling, failed test cases usually require drawing the entire image for debugging, which leads to a waste of time and manpower and reduces the efficiency of GPU verification.

Method used

Before rendering the image, the actual clipping parameters are forcibly modified to reduce the rendering area, rendering only the overlapping primitives, updating the primitive information, and then rendering to obtain a smaller image.

Benefits of technology

It reduces time and manpower costs and improves GPU verification efficiency.

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Abstract

This disclosure relates to the field of computer vision, proposing an image rendering method, apparatus, electronic device, and storage medium. The method includes: acquiring primitive information of each primitive in the current test case; acquiring a clipping mode and determining the actual clipping parameters of the current test case based on the clipping mode; clipping the primitives in the current test case according to the actual clipping parameters, and updating the primitive information based on the clipping result; and rendering the pixels in the actual rendering area according to the updated primitive information to obtain an image. When the current test case is a failed test case, the image rendering method of this disclosure can force modification of the actual clipping parameters before rendering the image, thereby rendering a smaller image, reducing time and labor costs, and improving GPU verification efficiency.
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