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bbc.com britishairways.com netdoctor.co.uk bgpa.wa.gov.au walkway.org 

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because it’s more fun than getting there in a straight line. home about me highlights contact testimonials string sorting in r appears to use different ordering from everyone else april 12th, 2018 | categories: c/c++ , matlab , programming , python , r | tags: update a discussion on twitter determined that this was an issue with locales . the practical upshot is that we can make r act the same way as the others by doing sys.setlocale("lc_collate", "c") which may or may not be what you should do! original post while working on a project that involves using multiple languages, i noticed some tests failing in one language and not the other. further investigation revealed that this was essentially because r's default sort order for strings is different from everyone else's. i have no idea how to say to r 'use the sort order that everyone else is using'. suggestions welcomed. r 3.3.2 sort(c("#b","-b","-a","#a","a","b")) [1] "-a" "-b" "#a" "#b" "a" "b" python 3.6 sorted({"#b","-b","-a","#a","a","b"}) ['#a', '#b', '-a', '-b', 'a', 'b'] matlab 2018a sort([{'#b'},{'-b'},{'-a'},{'#a'},{'a'},{'b'}]) ans = 1×6 cell array {'#a'} {'#b'} {'-a'} {'-b'} {'a'} {'b'} c++ int main(){ std::string mystrs[] = {"#b","-b","-a","#a","a","b"}; std::vector<std::string> stringarray(mystrs,mystrs+6); std::vector<std::string>::iterator it; std::sort(stringarray.begin(),stringarray.end()); for(it=stringarray.begin(); it!=stringarray.end();++it) { std::cout << *it << " "; } return 0; } result: #a #b -a -b a b share this: click to share on twitter (opens in new window) click to share on facebook (opens in new window) click to share on google+ (opens in new window) 0 comments research software engineer: a new career track? march 2nd, 2018 | categories: rse | tags: along with fellow fellow chris richardson, we wrote an article over at siam news about the emerging research software engineering profession. head over to research software engineer: a new career track? to check it out. if this has whetted your appetite for learning more about research software engineering then feel free to read the rse 2017 state of the nation report from last year. finally, i urge you to join the uk rse association if you have any interest in this area. share this: click to share on twitter (opens in new window) click to share on facebook (opens in new window) click to share on google+ (opens in new window) 1 comment strange matlab performance issue on microsoft azure f72s_v2 instances march 1st, 2018 | categories: cloud computing , hpc , making matlab faster , matlab | tags: i’m working on some matlab code at the moment that i’ve managed to reduce down to a bunch of implicitly parallel functions . this is nice because the data that we’ll eventually throw at it will be represented as a lot of huge matrices. as such, i’m expecting that if we throw a lot of cores at it, we’ll get a lot of speed-up. preliminary testing on local hpc nodes shows that i’m probably right. during testing and profiling on a smaller data set i thought that it would be fun to run the code on the most powerful single node i can lay my hands on. in my case that’s an azure f72s_v2 which i currently get for free thanks to a microsoft azure for research grant i won. these azure f72s_v2 machines are nice! running intel xeon platinum 8168 cpus with 72 virtual cores and 144gb of ram, they put my macbook pro to shame! theoretically, they should be more powerful than any of the nodes i can access on my university hpc system. so, you can imagine my surprise when the production code ran almost 3 times slower than on my macbook pro! here’s a microbenchmark, extracted from the production code, running on matlab 2017b on a few machines to show the kind of slowdown i experienced on these super powerful virtual machines. test_t = rand(8755,1); test_c = rand(5799,1); tic;test_res = bsxfun(@times,test_t,test_c');toc tic;test_res = bsxfun(@times,test_t,test_c');toc i ran the bsxfun twice and report the fastest since the first call to any function in matlab is often slower than subsequent ones for various reasons. this quick and dirty benchmark isn’t exactly rigorous but its good enough to show the issue. azure f72s_v2 (72 vcpus, 144 gb memory) running windows server 2016: 0.3 seconds azure f32s_v2 (32 vcpus, 64 gb memory) running windows server 2016: 0.29 seconds 2014 macbook pro running os x: 0.11 seconds dell xps 15 9560 laptop running windows 10: 0.11 seconds 8 cores on a node of sheffield university’s linux hpc cluster: 0.03 seconds 16 cores on a node of sheffield university’s linux hpc cluster: 0.015 seconds after a conversation on twitter , i ran it on azure twice — once on a 72 vcpu instance and once on a 32 vcpu instance. this was to test if the issue was related to having 2 physical cpus. the results were pretty much identical. the results from the university hpc cluster are more in line with what i expected to see — faster than a laptop and good scaling with respect to number of cores. i tried running it on 32 cores but the benchmark is still in the queue ;) what’s going on? i have no idea! i’m stumped to be honest. here are some thoughts that occur to me in no particular order maybe it’s an issue with windows server 2016. is there some environment variable i should have set or security option i could have changed? maybe the windows version of matlab doesn’t get on well with large core counts? i can only test up to 4 on my own hardware and that’s using windows 10 rather than windows server. i need to repeat the experiment using a linux guest os. is it an issue related to the fact that there isn’t a 1:1 mapping between physical hardware and virtual cores? intel xeon platinum 8168 cpus have 24 cores giving 48 hyperthreads so two of them would give me 48 cores and 96 hyperthreads. they appear to the virtualised os as 2 x 18 core cpus with 72 hyperthreads in total. does this matter in any way? share this: click to share on twitter (opens in new window) click to share on facebook (opens in new window) click to share on google+ (opens in new window) 0 comments creating a temporary, customised, multi-user hpc cluster for teaching using amazon aws and alces flight february 21st, 2018 | categories: cloud computing , hpc | tags: in a previous blog post , i told the story of how i used amazon aws and alcesflight to create a temporary multi-user hpc cluster for use in a training course. here are the details of how i actually did it. note that i have only ever used this configuration as a training cluster. i am not suggesting that the customisations are suitable for real work. before you start before attempting to use alcesflight on aws, i suggest that you ensure that you have the following things working a working aws account. ensure that you can create an ec2 virtual machine and connect to it via ssh. get the aws command line interface working. customizing the hpc cluster on aws alcesflight provides a cloudformation template for launching cluster instances on amazon aws. the practical upshot of this is that you answer a bunch of questions on a web form to customise your cluster and then you launch it. we are going to use this cloudformation template along with some bash scripts that provide additional customisation. get the customisation scripts the first step is to get some customization scripts in an s3 bucket. you could use your own or you could use the ones i created. if you use mine, make sure you take a good look at them first to make sure you are happy with what i’ve done! it’s probably worth using your own fork of my repo so you can customise your cluster further. it’s the bash scripts that allow the creation of a bunch of user accounts for trainees with randomized passwords. my scripts do some other things too and i’ve listed everything in the github readme.md . git clone https://github.com/mikecroucher/alces_flight_customisation cd alces_flight_customisation now you need to upload these to an s3 bucket. i called mine w

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Whois Information

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Whois Server Version 2.0

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Domain Name: WALKINGRANDOMLY.COM
Registrar: TUCOWS DOMAINS INC.
Sponsoring Registrar IANA ID: 69
Whois Server: whois.tucows.com
Referral URL: http://www.tucowsdomains.com
Name Server: NS1.SYSTEMDNS.COM
Name Server: NS2.SYSTEMDNS.COM
Name Server: NS3.SYSTEMDNS.COM
Status: clientTransferProhibited https://icann.org/epp#clientTransferProhibited
Status: clientUpdateProhibited https://icann.org/epp#clientUpdateProhibited
Updated Date: 06-jul-2017
Creation Date: 04-aug-2007
Expiration Date: 04-aug-2018

>>> Last update of whois database: 2017-07-15T06:43:10Z <<<

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  REGISTRAR TUCOWS DOMAINS INC.

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SERVERS

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DOMAIN

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STATUS
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