To follow up on some of this discussion... it seems the consensus (which is the direction I was leaning) is that the iMac is probably a better investment as an R workstation/desktop than the new MacPro. Setting up RStudio server is also an intriguing idea, but, at this point, my workflow tends to consist of bioinformatics/QIIME work on Linux servers -> R on desktop. But it would be nice to have a central installation so that I do not have to worry about keeping multiple installations (complete with tons of packages) consistent! FWIW, I did do a clean install on the laptop and performance is much, much, improved!
On Wed, Mar 12, 2014 at 11:03 AM, epi <[email protected]> wrote: > In my laptop settings i installed 2X8GB ram > and I replaced the dvd drive in favor of a second SSD drive (so to have > 2x512 GB SSD, 1TB in total) > using this sort of adaptors [1] > > Then i reinstalled OSX on a SW raid 0, with a sensible performance > improvement. > > Massimo. > > [1] > http://www.amazon.com/Adapter-Special-Designed-macbook-SuperDrive/dp/B0057V95M6 > > > On Mar 11, 2014, at 1:20 PM, Prof Brian Ripley <[email protected]> > wrote: > > On 11/03/2014 16:40, Simon Urbanek wrote: > > On Mar 11, 2014, at 10:35 AM, Stephen B. Cox <[email protected]> wrote: > > Anyone had any experience running fairly intensive analysis on a new > MacPro? I am looking to upgrade my desktop, and 80% of my time is spent in > RStudio/Latex/Sweave... working primarily with microbiome analysis (large > datasets). Been considering a new MacPro, but I am a little hesitant > about; a) moving my desktop to Mac, > > > 'large datasets' are in the eye of the beholder: you would need to > quantify that. > > That is typically a big plus - especially if you use Windows. It is in > fact probably the single major reason to pick a MacPro today, although I > would probably rather get an iMac in that case. > > > and b) whether the MacPro performance will be worth the cost (it almost > seems geared more towards graphics than anything else). > > > I don't have any hands-on experience with the new MacPro but its specs are > underwhelming. It is an experiment - if you can leverage the GPUs for > computing, then it may be worth it, but it's still quite hard to do so. > With AMD you'e essentially stuck with OpenCL and other than core support so > you can write your own kernels, there is very little else in R to leverage > that. Today, you're much better off getting a server/workstation which you > can load with RAM and more cores for computing for the same price (running > Linux, obviously, you really don't want to do computing on Windows with R) > - and use your desktop/laptop just to access its computing power. > > > For some background - I have worked on Macs for years, but moved my main > work desktop to Windows about 2 years ago. I also do quite a bit of work > in QIIME - which can be done on the mac (not the PC) and is both RAM and > CPU intensive... so, I can benefit from multiple cores, large RAM, etc. My > 2011 MacBook Pro seems extremely sluggish at this point when running basic > tasks (probably need to do a fresh OS install), > > > If you encounter sluggishness in OS X is pretty much always a disk issue. > Wipe the disk or even better put in a SSD - it's more than worth it - a > whole different world. > > > Or a 'fusion' drive in an iMac, which gives you enough SSD advantage > unless you really use repeatedly a lot of disc space (and works well for > me). The MacPro's I/O benchmarks are impressive, but you would need to be > able to generate data at those speeds to make use of them. > > > Cheers, > Simon > > > but the Windows machine has > never slowed down. This has added to some of my hesitation. > > Anyone have opinions/experience using R on the new MacPro? > > > On Mon, Mar 10, 2014 at 1:05 PM, Simon Urbanek > <[email protected]>wrote: > > > On Mar 10, 2014, at 12:43 PM, Nick <[email protected]> wrote: > > Good afternoon, I am looking at buying my first Mac and thought i'd ask > > for advice for what I should get. I have it down to the two models below > (but am open to realistic suggestions). > > > I will primarily be using R for machine learning packages, and the data > > sets are very large. If any other specs are needed let me know. > > > > "data sets are very large' - well, the machines listed below are certainly > not suitable to run anything on large data ;) so you may want to quantify > what you mean here. You want as much RAM as possible for large data since > that is the single item that will cause huge drop-off in performance when > exhausted and R certainly can take quite a bit of memory if this is really > your only machine to run computing on. Note that in modern Apple laptops > you cannot add more memory later, so this is rather important factor. > > Given a choice of the two MacBook Air is not a computing machine - it's > optimized for power consumption, not speed, so the only reason to go for it > is if you're looking for a light notebook and don't care about the > computing speed as much. > > Cheers, > Simon > > > > Thanks in advance. > > 13-inch MacBook Air ($1,349) > 1.7GHz Dual-Core Intel Core i7, Turbo Boost up to 3.3GHz > 8GB 1600MHz LPDDR3 SDRAM > 128GB Flash Storage > > 13-inch MacBook Pro with Retina ($1,399.00) > 2.4GHz Dual-core Intel Core i5, Turbo Boost up to 2.9GHz > 8GB 1600MHz DDR3L SDRAM > 128GB PCIe-based Flash Storage > [[alternative HTML version deleted]] > > _______________________________________________ > R-SIG-Mac mailing list > [email protected] > https://stat.ethz.ch/mailman/listinfo/r-sig-mac > > > _______________________________________________ > R-SIG-Mac mailing list > [email protected] > https://stat.ethz.ch/mailman/listinfo/r-sig-mac > > > [[alternative HTML version deleted]] > > _______________________________________________ > R-SIG-Mac mailing list > [email protected] > https://stat.ethz.ch/mailman/listinfo/r-sig-mac > > > _______________________________________________ > R-SIG-Mac mailing list > [email protected] > https://stat.ethz.ch/mailman/listinfo/r-sig-mac > > > > -- > Brian D. Ripley, [email protected] > Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ > University of Oxford, Tel: +44 1865 272861 (self) > 1 South Parks Road, +44 1865 272866 (PA) > Oxford OX1 3TG, UK Fax: +44 1865 272595 > > _______________________________________________ > R-SIG-Mac mailing list > [email protected] > https://stat.ethz.ch/mailman/listinfo/r-sig-mac > > > [[alternative HTML version deleted]] _______________________________________________ R-SIG-Mac mailing list [email protected] https://stat.ethz.ch/mailman/listinfo/r-sig-mac
