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The Mandelbrot example seems to make interpreted Python stand in for "the CPU performance"? If that's true, then I'm surprised they only see a 10x speed-up. I

The Mandelbrot example seems to make interpreted Python stand in for "the CPU performance"? If that's true, then I'm surprised they only see a 10x speed-up. I would expect more from only compiling that loop for the CPU. (Comparing to interpreted Python without numpy.) Given they already have a numba version, why not compile it for the CPU and compare? Also, they say consumer CPUs have 2-16 cores. (Who has 2 cores these days?) They go on suggest to rent an AWS GPU for $3 per hour. You're more likely to get 128 cores for that price, still on a single VM. Not saying it will be easy to write multi-threaded code for the CPU. But if you're lucky, the Python library you're using already does it.

lucb1e 3y ago
> Also, they say consumer CPUs have 2-16 cores. (Who has 2 cores these days?) Pretty sure my mom's laptop has 2 cores; I can't think of anyone whose daily driver has 16 cores. Real cores, not hyperthread stuff running at 0.3× the performance of a real core. As for the 128-core server system, note that those cores are typically about as powerful as a 2008 notebook. My decade-old laptop CPU outperforms what you get at DigitalOcean today, and storage performance is a similar story. The sheer number makes up for it, of course, but "number of cores" is not a 1:1 comparable metric. Agree, though, that the 10x speedup seems low. Perhaps, at 0.4s, a relatively large fraction of that time is spent on initializing the Python runtime (`time python3 -c 'print("1337")'` = 60ms), the module they import that needs to do device discovery, etc.? Hashcat, for example, takes like 15 seconds to get started even if it then runs very fast after that.
- 65a 3y ago
  My 2016 desktop had 22 cores and 44 threads. You can have the same processor for < $200 on ebay right now.
  - lucb1e 3y ago
    Cool, now I know one person :D I don't think the price matters btw. If 4 cores is all I need (I can't think of a desktop application that I use which benefits from more than 4 cores more than from faster cores, which is typically the trade-off at >4 real cores) then that's what I'd get because that's the optimum for my wallet and performance profile.

lucb1e 3y ago

> Also, they say consumer CPUs have 2-16 cores. (Who has 2 cores these days?) Pretty sure my mom's laptop has 2 cores; I can't think of anyone whose daily driver has 16 cores. Real cores, not hyperthread stuff running at 0.3× the performance of a real core. As for the 128-core server system, note that those cores are typically about as powerful as a 2008 notebook. My decade-old laptop CPU outperforms what you get at DigitalOcean today, and storage performance is a similar story. The sheer number makes up for it, of course, but "number of cores" is not a 1:1 comparable metric. Agree, though, that the 10x speedup seems low. Perhaps, at 0.4s, a relatively large fraction of that time is spent on initializing the Python runtime (`time python3 -c 'print("1337")'` = 60ms), the module they import that needs to do device discovery, etc.? Hashcat, for example, takes like 15 seconds to get started even if it then runs very fast after that.

65a 3y ago
My 2016 desktop had 22 cores and 44 threads. You can have the same processor for < $200 on ebay right now.
- lucb1e 3y ago
  Cool, now I know one person :D I don't think the price matters btw. If 4 cores is all I need (I can't think of a desktop application that I use which benefits from more than 4 cores more than from faster cores, which is typically the trade-off at >4 real cores) then that's what I'd get because that's the optimum for my wallet and performance profile.