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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? Given you are p
by glup 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? 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.