Highly efficient matrix transpose in Mojo
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Highly efficient matrix transpose in Mojo
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Re: Highly efficient matrix transpose in Mojo
#2I'm not an expert in this space, but is this meaningful? I'd assume that it's more common to fuse together transposition with an operation that precedes or follows it (e.g. matmul), which should be far more efficient than materializing the entire transposition in memory if it's just an intermediate value.
Re: Highly efficient matrix transpose in Mojo
#3Does anyone use Mojo in production at all or are even hiring for Mojo?
Re: Highly efficient matrix transpose in Mojo
#4Left unsaid, the 14% improvement in performance came at the cost of increasing dev time by 35%
Re: Highly efficient matrix transpose in Mojo
#5Mojos compiler is closed source. Thats a big no-no
Re: Highly efficient matrix transpose in Mojo
#6Mr. Mojo Risin'
Re: Highly efficient matrix transpose in Mojo
#7Where's the 14%? Looks like their final kernels show a 0.14% improvement of Mojo over the equivalent CUDA kernel?
Re: Highly efficient matrix transpose in Mojo
#8The "Switching to Mojo gave a 14% improvement over CUDA" title is editorialized, the original is "Highly efficient matrix transpose in Mojo".
Also, the improvement is 0.14%, not 14% making the editorialized linkbait particularly egregious.
Re: Highly efficient matrix transpose in Mojo
#9The "Switching to Mojo gave a 14% improvement over CUDA" title is editorialized, the original is "Highly efficient matrix transpose in Mojo". Also, the improvement is 0.14%, not 14% making the editorialized linkbait particularly egregious.
0.14% is within the limits of statistical error. So this is a nothing-"article".
Re: Highly efficient matrix transpose in Mojo
#10The "Switching to Mojo gave a 14% improvement over CUDA" title is editorialized, the original is "Highly efficient matrix transpose in Mojo". Also, the improvement is 0.14%, not 14% making the editorialized linkbait particularly egregious.
0.14% is within the limits of statistical error. So this is a nothing-"article".
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