Apple Neural Engine: Architecture, Programming, and Performance
11–20 of 30 posts
Re: Apple Neural Engine: Architecture, Programming, and Performance
#12Re: Apple Neural Engine: Architecture, Programming, and Performance
#13This scans very much as AI-written.
This is obvious Claude slop writing, the author would be advised to use vale [1] with samples of their own writing as a guide. > Performance begins with the roofline. On the M1 the engine holds about 12 fp16 TFLOP/s of compute against a DRAM-bandwidth ceiling. The roofline has a ridge point near 141 FLOP per byte, a 2 MB working-set threshold, a 0.23 ms floor under any single dispatch, and efficiency near 0.37 picojo…
Re: Apple Neural Engine: Architecture, Programming, and Performance
#14Earlier quoted context omitted.
This is obvious Claude slop writing, the author would be advised to use vale [1] with samples of their own writing as a guide. > Performance begins with the roofline. On the M1 the engine holds about 12 fp16 TFLOP/s of compute against a DRAM-bandwidth ceiling. The roofline has a ridge point near 141 FLOP per byte, a 2 MB working-set threshold, a 0.23 ms floor under any single dispatch, and efficiency near 0.37 picojo…
Please no. The author would be advised to write their own original thoughts.
Re: Apple Neural Engine: Architecture, Programming, and Performance
#15It does not seem to cover the Neural Accelerators, Apple's equivalent of the Tensor Cores. They only got released on M5 platform. This is probably the most important part to cover.
Re: Apple Neural Engine: Architecture, Programming, and Performance
#16Is there a non-slop version of this information available? I am reading up on GPU / ML micro architecture and am looking for some good sources.
Re: Apple Neural Engine: Architecture, Programming, and Performance
#17This Neural Engine seems useless for LLMs. Trapped in the wrong architecture
Re: Apple Neural Engine: Architecture, Programming, and Performance
#18Earlier quoted context omitted.
The burden of proof should be with the beholder. Must be so easy to scream AI when you don’t want to read an article.
You obviously haven't read it, because it is clunky garbage. > 19.4 Pacing compiles after a failure > A failed compile is not free of side effects on the shared compile service. A compile that fails restarts the service, which takes a few seconds to come back, and failures that keep arriving faster than the service can restart between them keep it from making progress, so unrelated compiles slow down until the failur…
Re: Apple Neural Engine: Architecture, Programming, and Performance
#19Re: Apple Neural Engine: Architecture, Programming, and Performance
#20Earlier quoted context omitted.
The burden of proof should be with the beholder. Must be so easy to scream AI when you don’t want to read an article.
You obviously haven't read it, because it is clunky garbage. > 19.4 Pacing compiles after a failure > A failed compile is not free of side effects on the shared compile service. A compile that fails restarts the service, which takes a few seconds to come back, and failures that keep arriving faster than the service can restart between them keep it from making progress, so unrelated compiles slow down until the failur…