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One of the main uses of a GPU is image (texture) sampling and processing. GPUs have specialized, built-in hardware to perform nearest-neighbor, bilinear, and bicubic filtering (with the VK_EXT_filter_cubic extension). However, some use cases require sampling with even larger kernels or with customized kernel weights. These cases can be manually implemented in a fragment or compute shader using the existing sampling instructions. However, that requires many round trips between the texture and shader units, which is not ideal from a power or performance perspective.
Our Qualcomm Developer Network YouTube channel continues growing as a valuable resource for development videos. Recently, we added several videos to the channel’s Windows on Snapdragon (WoS) playlist for Windows app developers:
Motion-based security systems are known for their high rate of false positives from events such as passing animals and the wind rustling nearby trees. It’s a use case ripe for AI, which can use computer vision and inference to weed out both false positives and false negatives. The result is more-accurate detection that increases profits by reducing the expenses associated with making in-person security checks.
How do you maintain backward compatibility with userspace apps in the Linux kernel? Most maintainers rely on code review and pushing changes out for testing. But with experienced reviewers and testing farms in short supply, it can be helpful to add automated tooling at build time to check for compatibility.
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