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For many linear algebra heavy workflows, (numpy, R, Julia, etc.) I expect that AMD and especially Intel processors with AVX-512 will crush the M1 on real-world
by tbenst 6y ago
For many linear algebra heavy workflows, (numpy, R, Julia, etc.) I expect that AMD and especially Intel processors with AVX-512 will crush the M1 on real-world benchmarks. But this isn’t a reflection of RISC vs CISC, and Apple could choose to add hardware acceleration for wider instructions and hopefully will in the future.
- glup 6y agoBut then again, if your workflow is linear algebra heavy, shouldn't you be doing that on a workstation or a cluster and not your little MacBook? Given you are probably doing that over Jupyter notebooks, SSH, or some cloud IDE, then the new ARM MacBooks will provide a better user experience?
- tbenst 6y agoI think we effectively agree with each other and the author. The M1 is better day-to-day processor but not a AMD/Intel killer for (edit: some) compute-heavy workflows...(yet?). Discussion more pertinent for Mac Pro, where current M1 would be worse than last gen Intel for some common workflows on those devices.
- judge2020 6y agoThe test will be the M1X Apple is apparently pushing for MBP or iMac usage[0]. 0: https://news.ycombinator.com/item?id=25225764 https://news.ycombinator.com/item?id=25225764
- sulam 6y agoI agree if you add the clarifying statement ...not an AMD/Intel killer for __some__ compute-heavy workflows... It’s clear there are other workflows which some people characterize as “compute-heavy” where the M1 is superior.
- tbenst 6y agoTotally fair, edited
- adolph 6y agoAn attached Intel processor for certain workflows is not unprecedented. Macintosh Quadra 610 DOS Compatible: Technical Specifications https://support.apple.com/kb/SP227?locale=en_US https://support.apple.com/kb/SP227?locale=en_US Pictures: http://www.applefool.com/applefool/Quadra_610_%28DOS_Compatible%29.html#17 http://www.applefool.com/applefool/Quadra_610_%28DOS_Compati...
- dragontamer 6y ago> But then again, if your workflow is linear algebra heavy, shouldn't you be doing that on a workstation or a cluster and not your little MacBook? Blender, Gimp / Photoshop, Video Editing, LTSpice / PSpice and Matlab come to mind. These are consumer-ish workflows that benefit from linear algebra, but people want to do them on their laptops. Hell, people are doing video editing on their PHONES these days, due to the convenience. ---------- Workstations and clusters are not affordable for the vast majority of users. GPUs probably are affordable however. But these programs aren't really operating on GPUs yet (I mean, Blender and some Video Editing programs are... but LTSpice / Matlab are CPU-only still)
- chalst 6y agoClusters are affordable, given that cloud hosting is a commodity now. Digital Ocean, for instance, charge nothing for traffic between nodes if they are hosted at the same data centre. Julia, in particular, has the interesting-looking JuliaHub service in the pipeline: https://www.youtube.com/watch?v=JVUJ5Oohuhs&feature=youtu.be&t=256 https://www.youtube.com/watch?v=JVUJ5Oohuhs&feature=youtu.be...
- CyberDildonics 6y agoThat's not compute and has nothing to do with the latency and bandwidth you would need to have the same interactivity. Digital Ocean moving data internally for free has nothing to do with offloading video editing from a laptop.
- imtringued 6y agoA lot of cloud GPU providers charge $1000 per node per month. Also AWS and GCP are not providing a commodity service. They charge hefty margins.
- Abishek_Muthian 6y ago>if your workflow is linear algebra heavy, shouldn't you be doing that on a workstation or a cluster and not your little MacBook? Not necessarily, such math & ML inference workloads are done even done on a Raspberry pi, other ARM SBCs for numerous CV and other projects requiring edge compute.
- deleted 6y ago[deleted]
- nl 6y agoI do local work in numpy/pandas all the time on my MPB. Large data size or ML training is where I use my cluster and/or GPU computers.
- lock-free 6y agoAVX 512 isn't available on consumer CPUs, it's not relevant here.
- klelatti 6y agoAVX 512 has been on some consumer CPUs since last year (e.g. Ice Lake in Surface Laptop 3).
- mtgx 6y agoAnd for how many total seconds is it useful in a form factor like that before it throttles down? This is why Apple never adds a spec just for the sake of it.
- w0utert 6y agoIce Lake, as for example found in the 13” Intel MBP Apple stills sells, has AVX-512
- trimbo 6y agoAs well as Tiger Lake (though those aren't in Macs)
- marmaduke 6y agoIt’s available in the MacBook Air 2020 Intel version, and it works well.
- q-big 6y ago> I expect that AMD and especially Intel processors with AVX-512 AMD processors do not support AVX-512 (yet?).
- PartiallyTyped 6y agoIIRC 2x256 on 3xxx series. Doubt a 1x512 is available on 5xxx series.
- Hello71 6y ago(AMD processors) AND (Intel processors with AVX-512)
- gruez 6y agodoesn't seem to be https://en.wikipedia.org/wiki/AVX-512#CPUs_with_AVX-512 https://en.wikipedia.org/wiki/AVX-512#CPUs_with_AVX-512
- mtgx 6y agoM2 will likely support Arm's new flexible SVA2 instructions.
- marmaduke 6y agoGiven the Intel MBA 2020 shipped with AVX512 this would even be a fair comparison.
- tbenst 6y agoAnandtech / Tom’s Hardware, if you’re there, please do this!!
- deleted 6y ago[deleted]
- Jap2-0 6y agoIt looks like simdjson doesn't support AVX-512, so there couldn't be a direct comparison with this article. I recently got a Tiger Lake laptop, though, so if anyone has a good means for comparison I'd be interested.