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@ -511,4 +511,3 @@ This project started after seeing that a lot of new and renowned ML & DL project
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The Vulkan SDK offers a great low level interface that enables for highly specialized optimizations - however it comes at a cost of highly verbose code which requires 500-2000 lines of code to even begin writing application code. This has resulted in each of these projects having to implement the same baseline to abstract the non-compute related features of the Vulkan SDK. This large amount of non-standardised boiler-plate can result in limited knowledge transfer, higher chance of unique framework implementation bugs being introduced, etc.
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We are currently developing Kompute not to hide the Vulkan SDK interface (as it's incredibly well designed) but to augment it with a direct focus on the Vulkan SDK's GPU computing capabilities. [This article](https://towardsdatascience.com/machine-learning-and-data-processing-in-the-gpu-with-vulkan-kompute-c9350e5e5d3a) provides a high level overview of the motivations of Kompute, together with a set of hands on examples that introduce both GPU computing as well as the core Kompute architecture.
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@ -10,4 +10,3 @@ Kompute aims to follow the two following policies:
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## Reporting a Vulnerability
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If you identify a vulnerability the best way to report it is by sending an email to the team via a@ethical.institute. The discussion can then take place there on next steps (ie updating library, reaching out to 3rd party projects, etc).
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