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I suspect your main motivator is to want to build a PC. Chances are that the extra computational power or cores won't actually make your work faster for day to

by matt_s 10y ago

I suspect your main motivator is to want to build a PC. Chances are that the extra computational power or cores won't actually make your work faster for day to day use. Building a PC is fun and you will be able to do piece-meal upgrades as you want instead of having to replace an entire laptop because it becomes outdated. Financially it might make sense since you have one time expenses like case, power supply, peripherals and then things you can upgrade at will like motherboard, cpu, ram, and drives. If you future-proof the motherboard purchase (buying best or high-end now) then future CPU updates would just require a new CPU. The downside of building a PC is that new stuff is coming out every year without much actual progress regarding speed. And mobility is a downside if you need something in class (you mentioned you were in school) or to go somewhere to work on a project collaboratively or if you move a lot. If you can, keep the laptop and build a PC. Then you can connect to more compute power if you need it, assuming you setup a way to connect to it from the internet.

terminalcommand 10y ago
Thanks for the detailed answer. I had been thinking about this for so long that I've forgetten the actual reason I even wanted to build a desktop. It was to get the experience selecting and putting the pieces together, having control over the hardware. As for remote connection, I can setup a way to connect to it from the internet as I manage my own VPN on a cheap server. I definitely want to build a PC and my laptop is going nowhere.
EduardoBautista 10y ago
> If you future-proof the motherboard purchase (buying best or high-end now) then future CPU updates would just require a new CPU. Unless the CPU socket changes.
- majewsky 10y ago
  That's why 2017 is not a bad year for a motherboard purchase: AMD will come out with their new AM4 socket pretty soon, and Intel will probably retain the LGA 1151 socket introduced with Skylake in 2015/16 for a few more years.
- matt_s 10y ago
  Yeah that'll get you. My builds tend to be years apart so it's more of a replace everything scenario. It is fun to look at the new tech coming out and day-dream of pimp-my-pc scenarios. I still think daily work doesn't improve much with CPU/mobo changes for most developers though. Especially if it is web related development since you will likely be running on virtualized servers anyhow.
problems 10y ago
> I suspect your main motivator is to want to build a PC. Chances are that the extra computational power or cores won't actually make your work faster for day to day use. Another potential factor - If you play games or develop 3d applications, high end GPUs are much more affordable in desktop form factors than in laptop ones and generally have more horsepower than their laptop equivalents. If you do a lot of video encoding for live streaming or media creation you may also benefit from this (seriously a GTX 1080 can encode 1080p HEVC at 300 FPS). The cost is also generally lower for comparable hardware if you do a DIY desktop than a laptop. While this might not be relevant to OP, it may be relevant to other people in a similar situation.
- inetsee 10y ago
  This may not be relevant to the OP, but I'm interested in machine learning, and having a graphics card with a big GPU is important. Serious machine learning computers have sky high prices, but for learning, you can get a graphics card with 640 or more gpu cores for $250 or less. I don't know of any laptops in the requested price range that have that kind of gpu power. Of course, a big graphics card can also be used for graphics work, including video encoding, not just video games.
  - problems 10y ago
    Yeah, there's a quite broad spectrum of GPGPU applications these days, Wikipedia has a fairly comprehensive list to consider: https://en.wikipedia.org/wiki/General-purpose_computing_on_graphics_processing_units#Applications https://en.wikipedia.org/wiki/General-purpose_computing_on_g... If you're interested in any of these and don't need the mobility for another reason, a desktop may be a very good consideration indeed.
  - cr0sh 10y ago
    For my current involvement of taking the Udacity Self-Driving Car Engineer Nanodegree, I'm currently using a 750 Ti SC card - which was what I had in my current workstation at home. I've found that it performs adequately (so far) for what I am doing. I'm running Ubuntu 14.04 LTS, and I installed CUDA and CUDANN (and other junk) to run Python/TensorFlow with GPU support. That said, I'm currently working on the behavioral cloning project (teach a virtual car to drive using what we've learned so far), and given the amount of data we'll gather (10s of thousands of frames we have to process) to train our models - I tend to wonder if I will need to upgrade. Fortunately, that won't be too difficult for me - I have both a 960 and 970 waiting in the wings; they were cards originally destined for a mini-itx gaming machine build that I've never gotten around to (hmm - maybe I should just build it for my next workstation instead). Also - 960s and 970s are dropping in price like a rock, since the hardcore gamers are moving to the 10xx line; while they may not have as many cores or as much speed, they are still very capable cards for ML purposes. I've also been considering getting a multi-pcie slot server motherboard (maybe with dual xeons or such - these mobo combos are actually pretty cheap on ebay), and dropping in one of those cards, then later adding on more GPU cards - strictly for an ML box...

by matt_s 10y ago

terminalcommand 10y ago

Thanks for the detailed answer. I had been thinking about this for so long that I've forgetten the actual reason I even wanted to build a desktop. It was to get the experience selecting and putting the pieces together, having control over the hardware. As for remote connection, I can setup a way to connect to it from the internet as I manage my own VPN on a cheap server. I definitely want to build a PC and my laptop is going nowhere.

EduardoBautista 10y ago

> If you future-proof the motherboard purchase (buying best or high-end now) then future CPU updates would just require a new CPU. Unless the CPU socket changes.

majewsky 10y ago
That's why 2017 is not a bad year for a motherboard purchase: AMD will come out with their new AM4 socket pretty soon, and Intel will probably retain the LGA 1151 socket introduced with Skylake in 2015/16 for a few more years.
matt_s 10y ago
Yeah that'll get you. My builds tend to be years apart so it's more of a replace everything scenario. It is fun to look at the new tech coming out and day-dream of pimp-my-pc scenarios. I still think daily work doesn't improve much with CPU/mobo changes for most developers though. Especially if it is web related development since you will likely be running on virtualized servers anyhow.

problems 10y ago

> I suspect your main motivator is to want to build a PC. Chances are that the extra computational power or cores won't actually make your work faster for day to day use. Another potential factor - If you play games or develop 3d applications, high end GPUs are much more affordable in desktop form factors than in laptop ones and generally have more horsepower than their laptop equivalents. If you do a lot of video encoding for live streaming or media creation you may also benefit from this (seriously a GTX 1080 can encode 1080p HEVC at 300 FPS). The cost is also generally lower for comparable hardware if you do a DIY desktop than a laptop. While this might not be relevant to OP, it may be relevant to other people in a similar situation.

inetsee 10y ago
This may not be relevant to the OP, but I'm interested in machine learning, and having a graphics card with a big GPU is important. Serious machine learning computers have sky high prices, but for learning, you can get a graphics card with 640 or more gpu cores for $250 or less. I don't know of any laptops in the requested price range that have that kind of gpu power. Of course, a big graphics card can also be used for graphics work, including video encoding, not just video games.
- problems 10y ago
  Yeah, there's a quite broad spectrum of GPGPU applications these days, Wikipedia has a fairly comprehensive list to consider: https://en.wikipedia.org/wiki/General-purpose_computing_on_graphics_processing_units#Applications https://en.wikipedia.org/wiki/General-purpose_computing_on_g... If you're interested in any of these and don't need the mobility for another reason, a desktop may be a very good consideration indeed.
- cr0sh 10y ago
  For my current involvement of taking the Udacity Self-Driving Car Engineer Nanodegree, I'm currently using a 750 Ti SC card - which was what I had in my current workstation at home. I've found that it performs adequately (so far) for what I am doing. I'm running Ubuntu 14.04 LTS, and I installed CUDA and CUDANN (and other junk) to run Python/TensorFlow with GPU support. That said, I'm currently working on the behavioral cloning project (teach a virtual car to drive using what we've learned so far), and given the amount of data we'll gather (10s of thousands of frames we have to process) to train our models - I tend to wonder if I will need to upgrade. Fortunately, that won't be too difficult for me - I have both a 960 and 970 waiting in the wings; they were cards originally destined for a mini-itx gaming machine build that I've never gotten around to (hmm - maybe I should just build it for my next workstation instead). Also - 960s and 970s are dropping in price like a rock, since the hardcore gamers are moving to the 10xx line; while they may not have as many cores or as much speed, they are still very capable cards for ML purposes. I've also been considering getting a multi-pcie slot server motherboard (maybe with dual xeons or such - these mobo combos are actually pretty cheap on ebay), and dropping in one of those cards, then later adding on more GPU cards - strictly for an ML box...