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Joined 2 years ago
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Cake day: July 13th, 2023

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  • Where to begin… I think numerous sources already discuss what is bad about Amazon, the shopping website, and its CEO. One among many other issues, which I think shows best what Amazon’s values are: for all the resources they have, the Amazon website is terrible to use, and it’s done on purpose. Search filters are useless, promoted products show up everywhere… The website isn’t designed for you to find the things you want, it’s designed for you to buy what somebody else wants to sell. This isn’t a business model I care for, and if that’s what the company is about, I don’t want anything to do with them or any of their products, no matter how good or popular.




  • Thank you for the nuanced answer!

    You ask why I feel this is less secure: it seems the lowest possible bar when it comes to controlling what gets installed on your system. The script may or may not give you a choice as to where things get installed. It could refuse to install or silently overwrite stuff if something already exists. If install fails, it may or may not leave data behind, in directories I may or may not know about. It may or may not run a checksum on the downloaded data before installing. Because it’s a competely free-form script, there is no standard I can expect. For an application, I would read the documentation to learn more, but these scripts are not normally documented (other than “use this to install”). That uncertainty, to me, is insecure/unsafe.





  • How I wish CUDA was an open standard. We use it at work, and the tooling is a constant pain. Being almost entirely controlled by NVIDIA, there’s no alternative toolset, and that means little pressure to make it better. Clang being able to compile CUDA code is an encouraging first step, meaning we could possibly do without nvcc. Sadly the CMake support for it on Windows has not yet landed. And that still leaves the SDK and runtime entirely in NVIDIA’s hands.

    What irritates me the most about this SDK is the versioning and compatibility madness. Especially on Windows, where the SDK is very picky about the compiler/STL version, and hence won’t allow us to turn on C++20 for CUDA code. I also could never get my head around the backward/forward compatibility between SDK and hardware (let alone drivers).

    And the bloat. So many GBs of pre-compiled GPU code for seemingly all possible architectures in the runtime (including cudnn, cublas, etc). I’d be curious about the actual number, but we probably use 1% of this code, yet we have to ship the whole thing, all the time.

    If CPU vendors were able to come up with standard architectures, why can’t GPU vendors? So much wasted time, effort, energy, bandwidth, because of this.

    How do you people manage this?