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2023-01-26.log
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<rekado>the claims in this article give me hope <rekado>“The aim of Triton is to provide an open-source environment to write fast code at higher productivity than CUDA” <civodul>reading this kind of article about market shares and all gives a weird feeling <civodul>i guess it relies on the proprietary nvidia stuff anyway <rekado>yeah, all that market share crap makes my eyes glaze over <rekado>I just see what I want to see: first mover advantage has been squandered by both Google and NVIDIA <rekado>Triton compiles to PTX instructions, so it’s the lower level that’s also targeted by nvcc for CUDA. <rekado>if it’s true that CUDA and Tensorflow loose mind share that’s a good thing in my opinion. <rekado>the world of impenetrable huge frameworks with billions in investment sure is strange, though <civodul>i've been hoping for 10y to see CUDA fade away <civodul>i thought we were getting there with Xeon Phi <civodul>then there was OpenCL, Vulkan, now AMD <civodul>let's believe in the tenth-mover advantage :-) <rekado>CUDA got one thing right: it’s easy to install and use <rekado>to this day I have no mental model of all the moving parts in opencl or rocm <civodul>sysadmins at work seem to never be quite sure they got it right <rekado>I *wanted* us to use OpenCL back then but just couldn’t figure out how to even get started <civodul>yeah so CUDA is easy in the sense that it's a complete homogeneous stack <rekado>and the popularity of tensorflow meant that nobody would use it seriously anyway <rekado>I’m happy that tensorflow is no longer the only “serious” framework in use <rekado>in our group everyone has moved on to pytorch <civodul>i'm happy if that lets us forget about Bazel :-) <rekado>pytorch certainly wasn’t easy to package — but I’ll take it over bootstrapping all that java stuff for bazel and *then* figure out how to actually build a bazel build system… <civodul>but yeah, still in the "impenetrable framework" space, as you wrote <rekado>but overall I have mixed feelings about the current iteration of AI enthusiasm <rekado>it’s so far outside the realm of free software <rekado>expensive hardware —> cloud platforms <civodul>that's the thing, it makes me anxious rather than enthusiastic <rekado>lots of money –> big corporations steering the stack <civodul>plus an energy drain, with some applications being questionable <civodul>i hate it when machine learning is used in situations where an analytical solution could be worked on <rekado>re energy drain: it annoys me that this massive computing problem is set up within the adversarial framework of competition <rekado>we could have had massively distributed collaborative computing <civodul>most uses are about making money one way or another anyway no? <rekado>I’m not very familiar with all the use cases <rekado>I know of the usual surveillance suspects, but what I’m most familiar with is bio research. <civodul>i suspect scientific applications don't weigh much in term of resource usage compared to the various surveillance applications <civodul>imagine the ChatGPT budget for a single day :-) <rekado>“average is probably single-digits cents per chat; trying to figure out more precisely and also how we can optimize it” <rekado>and recent news are that Microsoft now “donates” Azure GPU time (with the implication that OpenAI’s ChatGPT is now essentially locked into an Azure dependency) <civodul>it's also competing a bit with their own AutoPilot thing