Search Results

Search found 415 results on 17 pages for 'bottleneck'.

Page 11/17 | < Previous Page | 7 8 9 10 11 12 13 14 15 16 17  | Next Page >

  • Why is Double.Parse so slow?

    - by alexhildyard
    I was recently investigating a bottleneck in one of my applications, which read a CSV file from disk using a TextReader a line at a time, split the tokens, called Double.Parse on each one, then shunted the results into an object list. I was surprised to find it was actually the Double.Parse which seemed to be taking up most of the time.Googling turned up this, which is a little unfocused in places but throws out some excellent ideas:It makes more sense to work with binary format directly, rather than coerce strings into doublesThere is a significant performance improvement in composing doubles directly from the byte stream via long intermediariesString.Split is inefficient on fixed length recordsIn fact it turned out that my problem was more insidious and also more mundane -- a simple case of bad data in, bad data out. Since I had been serialising my Doubles as strings, when I inadvertently divided by zero and produced a "NaN", this of course was serialised as well without error. And because I was reading in using Double.Parse, these "NaN" fields were also (correctly) populating real Double objects without error. The issue is that Double.Parse("NaN") is incredibly slow. In fact, it is of the order of 2000x slower than parsing a valid double. For example, the code below gave me results of 357ms to parse 1000 NaNs, versus 15ms to parse 100,000 valid doubles.            const int invalid_iterations = 1000;            const int valid_iterations = invalid_iterations * 100;            const string invalid_string = "NaN";            const string valid_string = "3.14159265";            DateTime start = DateTime.Now;                        for (int i = 0; i < invalid_iterations; i++)            {                double invalid_double = Double.Parse(invalid_string);            }            Console.WriteLine(String.Format("{0} iterations of invalid double, time taken (ms): {1}",                invalid_iterations,                ((TimeSpan)DateTime.Now.Subtract(start)).Milliseconds            ));            start = DateTime.Now;            for (int i = 0; i < valid_iterations; i++)            {                double valid_double = Double.Parse(valid_string);            }            Console.WriteLine(String.Format("{0} iterations of valid double, time taken (ms): {1}",                valid_iterations,                ((TimeSpan)DateTime.Now.Subtract(start)).Milliseconds            )); I think the moral is to look at the context -- specifically the data -- as well as the code itself. Once I had corrected my data, the performance of Double.Parse was perfectly acceptable, and while clearly it could have been improved, it was now sufficient to my needs.

    Read the article

  • Profiling Startup Of VS2012 &ndash; Ants Profiler

    - by Alois Kraus
    I just downloaded ANTS Profiler 7.4 to check how fast it is and how deep I can analyze the startup of Visual Studio 2012. The Pro version which is useful does cost 445€ which is ok. To measure a complex system I decided to simply profile VS2012 (Update 1) on my older Intel 6600 2,4GHz with 3 GB RAM and a 32 bit Windows 7. Ants Profiler is really easy to use. So lets try it out. The Ants Profiler does want to start the profiled application by its own which seems to be rather common. I did choose Method Level timing of all managed methods. In the configuration menu I did want to get all call stacks to get full details. Once this is configured you are ready to go.   After that you can select the Method Grid to view Wall Clock Time in ms. I hate percentages which are on by default because I do want to look where absolute time is spent and not something else.   From the Method Grid I can drill down to see where time is spent in a nice and I can look at the decompiled methods where the time is spent. This does really look nice. But did you see the size of the scroll bar in the method grid? Although I wanted all call stacks I do get only about 4 pages of methods to drill down. From the scroll bar count I would guess that the profiler does show me about 150 methods for the complete VS startup. This is nonsense. I will never find a bottleneck in VS when I am presented only a fraction of the methods that were actually executed. I have also tried in the configuration window to also profile the extremely trivial functions but there was no noticeable difference. It seems that the Ants Profiler does filter away way too many details to be useful for bigger systems. If you want to optimize a CPU bound operation inside NUnit then Ants Profiler is with its line level timings a very nice tool to work with. But for bigger stuff it is certainly not usable. I also do not like that I must start the profiled application from the profiler UI. This makes it hard to profile processes which are started by some other process. Next: JetBrains dotTrace

    Read the article

  • ClearTrace Performance on 170GB of Trace Files

    - by Bill Graziano
    I’ve always worked to make ClearTrace perform well.  That’s probably because I spend so much time watching it work.  I’m often going through two or three gigabytes of trace files but I rarely get the chance to run it on a really large set of files. One of my clients wanted to run a full trace for a week and then analyze the results.  At the end of that week we had 847 200MB trace files for a total of nearly 170GB. I regularly use 200MB trace files when I monitor production systems.  I usually get around 300,000 statements in a file that size if it’s mostly stored procedures.  So those 847 trace files contained roughly 250 million statements.  (That’s 730 bytes per statement if you’re keeping track.  Newer trace files have some compression in them but I’m not exactly sure what they’re doing.)  On a system running 1,000 statements per second I get a new file every five minutes or so. It took 27 hours to process these files on an older development box.  That works out to 1.77MB/second.  That means ClearTrace processed about 2,654 statements per second. You can query the data while you’re loading it but I’ve found it works better to use a second instance of ClearTrace to do this.  I’m not sure why yet but I think there’s still some dependency between the two processes. ClearTrace is almost always CPU bound.  It’s really just a huge, ugly collection of regular expressions.  It only writes a summary to its database at the end of each trace file so that usually isn’t a bottleneck.  At the end of this process, the executable was using roughly 435MB of RAM.  Certainly more than when it started but I think that’s acceptable. The database where all this is stored started out at 100MB.  After processing 170GB of trace files the database had grown to 203MB.  The space savings are due to the “datawarehouse-ish” design and only storing a summary of each trace file. You can download ClearTrace for SQL Server 2008 or test out the beta version for SQL Server 2012.  Happy Tuning!

    Read the article

  • How to Apache SSL proxy to openerp 7 running in VM?

    - by Johnbritto
    I have installed openerp v7 in an ubuntu 12.04 Virtual machine from launchpad.i.e server, web, addons. I configured SSL reverse proxy on virtual machine and my configuration for virtual host *:443 are ServerName openerp.mydomain.net ServerAdmin openerp@localhost SSLEngine on SSLCertificateFile /etc/ssl/openerp/server.crt SSLCertificateKeyFile /etc/ssl/openerp/server.key ProxyRequests Off ProxyPreserveHost On <Proxy *> Order deny,allow Allow from all </Proxy> ProxyVia On ProxyPass / http://172.16.150.14:8069/ ProxyPassReverse / http://172.16.150.14:8069/ RequestHeader set "X-Forwarded-Proto" "https" # Fix IE problem (httpapache proxy dav error 408/409) SetEnv proxy-nokeepalive 1 </VirtualHost> on host, I have configured apache reverse proxy for my subdomain in vhost_ssl.conf as SSLEngine On SSLProxyEngine On ProxyRequests Off ProxyPreserveHost On <Proxy *> Order deny,allow Allow from all </Proxy> ProxyPass / https://172.16.150.14/ ProxyPassReverse / https://172.16.150.14/ SetEnv proxy-nokeepalive 1 <Location /> Order allow,deny Allow from all </Location> I have set 172.16.150.14 on netrpc and xmlrcs interfaces in openerp-server.conf. Now, when I access https:// openerp.mydomain.net from Girefox and chrome browser..I get http:// openerp.mydomain.net%2C%20openerp.mydomain.net/?db=testingdb which makes 404. But when i access URL from IE 9, the URL https:// openerp.mydomain.net works ok .. secondly if i change the parameter list_db= false, then the links works as expected.. Kindly let me know what is creating bottleneck with URL redirect to http://openerp.mydomain.net, openerp.myydomain.net/?db=testdb on Firefox and chrome. i am struck here doing troubleshooting with the URL to work.

    Read the article

  • Latency between IIS and SQL on same physical, two VMs

    - by Jerad Rose
    I have a single server (2x4 core CPUs, 32GB ram), that is a Windows Server 2012 Hyper V host, and it hosts two guest VMs (also Windows Server 2012 instances). One of them is a web server, the other is a SQL server. When hitting a page that loops over 50 records, there is noticeable latency. I capture/report the timings of each iteration on the loop, and each iteration is about 20-30 milliseconds. Of course, this amounts to over a second of latency for the whole loop. I thought maybe SQL needed to be tuned, but running profiler on it, the queries are showing almost 0 duration, so it seems the bottleneck is in transit between the two VMs. I have both VMs configured to use the actual NIC (vs. using a VNIC), so maybe that's part of my problem. Also, this is a classic ASP site, so it's using the SQL OLE DB provider, and I'm wondering if that is part of the problem. This is a new server setup, from an existing Windows 2003/IIS6 server setup where both web and DB run on the same server instance (no virtualization). On that setup, there is no such latency when looping over the cursor like this. But there are so many variables, I'm not sure where to start ruling things out.

    Read the article

  • Performance mitigations serving content from a UNC share via IIS 6

    - by codepoke
    I have a quad processor vmware instance running Windows 2003 and 1gb ethernet. I'm comparing serving the exact same heavy .NET 2.0 content from the local hard drive versus serving it from a UNC drive. If I use WCAT to load it down, I see about a 40% reduction in transactions/sec while serving from the UNC. Processor time barely moves from 45% and the NIC sits around 40% either way. I don't see any significant memory loading either way. Context Switches/Transaction, though, more than doubles when serving from the UNC. Pathlengths more than double as well, but I believe that's just an expression of the effect of context switching. All told, it looks like the bottleneck is processor switching while waiting on content from the UNC share. Is my experience about the norm? Is there some mitigation I might try? I twiddled HKLM\System\CurrentControlSet\Services\LanmanWorkstation\Parameters\MaxCmds a little bit per http://technet.microsoft.com/en-us/library/dd296694(WS.10).aspx, but to no obvious effect. I kind of doubt my problem is lack of connections, but rather just the act of switching from thread to thread while waiting on data.

    Read the article

  • Computer specs for a large database

    - by SpeksETC
    What sort of computer specs (CPU, RAM, disk speed) should I use for running queries on a database of 200+ million records? The queries are for a research project, so there is only one "user" and only one query will be running at a time. I tried it on my own laptop with SQL Server with an i3 processor, 2GB RAM, 5400 RPM disk and a simple query didn't finish even after 8+ hours. I have an option to connect a SSD via eSata and upgrade to 4GB RAM, but not sure if this will be enough... Thanks! Edit: The database is about 25 GB and the indexes are not setup properly. When I tried to add an index, I let it run for about 8 hours and it still hadn't finished so I gave up. Should I have more patience :)? In general, the queries will run once in a while and its ok even if it takes a couple hours to complete.... Also, the queries will produce probably about 10 million records which I need to process using Stata/Matlab and I'm concerned that my current laptop is not strong enough, but unsure of the bottleneck....

    Read the article

  • Distribute IP packets accross different NIC queues with MSI (Message Signalled Interrupts)

    - by Ansis Atteka
    NetXtreme II BCM5709 Gigabit Ethernet NIC supports MSI feature (Message Signaled Interrupts) and it has 8 queues. Each queue has its own Interrupt handler in /proc/interrupts. What I am trying to accomplish is to tell NIC which packets should go to which queue. Questions: Is it possible to manually specify which IP packets should go to which queue by encapsulated protocol type (e.g. IPsec packets go in one queue, while TCP packets go in another queue)? If it is possible - how can I do it under Linux? If it is not possible - should I look at MSI-X capable NIC cards to solve this problem? More details: We have one Interface that is terminating IPSec and forwarding/terminating TCP connections. The IPSec packet decryption is inlined (this means that decryption is done under the same ksoftirqd/X context). We are trying to find out if we will be able to improve total performance if IPSec packets will be scheduled on another CPU than TCP packets. One more limitation is that IPSec code is not MP-safe, hence I can not run it under more than one ksoftirqd/X. By default it seems that packets are distributed/hashed by source IP over the 8 NIC queues. The bottleneck is IPSec that chokes out TCP traffic while it is decrypting/encrypting IPSec packets at ~100% CPU. OS is Ubuntu 10.10 (2.6.32-27-server) and NIC is Broadcom BCM5709.

    Read the article

  • How to direct reverse proxy requests using wildcard vhosts

    - by HonoredMule
    I'm interested in running a reverse proxy with 2-3 virtual machines behind it. Each internal server will run multiple virtual hosts, and rather than manually configuring each individual vhost on the proxy (a variety of vhosts come and go too often for this to be practical), I would like to use something which can employ pattern matching in a sequential order to find the appropriate back-end server. For example: Server 1: *.dev.mysite.com Server 2: *.stage.mysite.com Server 3: *.mysite.com, dev.mysite.com, stage.mysite.com, mysite.com Server 4: * In the above configuration, task.dev.mysite.com would go to Server 1, dev.mysite.com would go to Server 3, yoursite.stage.mysite.com to Server 2, www.mysite.com to Server 3, and yoursite.com to Server 4. I've looked into using Squid, Varnish, and nginx so far. I have my opinions regarding their respective desirability and general suitability, but it's not readily apparent if any of them can handle dynamic server selection in this manner and not require per-vhost configuration. Apache on the other hand can do this handily and simply, but otherwise (aside from being well-known and familiar) seems very poorly suited to the partly-performance-serving task. Performance isn't actually a major concern yet, but it seems foolish to use Apache if another system will perform far better and can also handle the desired 'hands-free' configuration. But so is frequently having to adjust the gateway for all production services and risk network-wide outage...and so also is setting oneself up for longer downtime later if Apache becomes a too-small bottleneck. Which of these (or other) reverse proxies can do it/would do it best? And maybe I should post this as a separate question, but if Apache is the only practical option, how safe/reliable/predictable is apache-mpm-event in apache2.2 (Ubuntu 12.04.1) particularly for a dedicated reverse proxy? As I understand it the Event MPM was declared "safe" as of 2.4 but it's unclear whether reaching stability in 2.4 has any implications for the older (2.2) versions available in official/stable package channels of various distros.

    Read the article

  • Packet drop measured by ethtool, tcpdump and ifconfig

    - by Rayne
    Hi all, I have a question regarding packet drops. I am running a test to determine when packet drops occur. I'm using a Spirent TestCenter through a switch (necessary to aggregate Ethernet traffic from 5 ports to one optical link) to a server using a Myricom card. While running my test, if the input rate is below a certain value, ethtool does not report any drop (except dropped_multicast_filtered which is incrementing at a very slow rate). However, tcpdump reports X number of packets "dropped by kernel". Then if I increase the input rate, ethtool reports drops but "ifconfig eth2" does not. In fact, ifconfig doesn't seem to report any packet drops at all. Do they all measure packet drops at different "levels", i.e. ethtool at the NIC level, tcpdump at the kernel level etc? And am I right to say that in the journey of an incoming packet, the NIC level is the "so-called" first level, then the kernel, then the user application? So any packet drop is likely to happen first at the NIC, then the kernel, then the user application? So if there is no packet drop at the NIC, but packet drop at the kernel, then the bottleneck is not at the NIC? Thank you. Regards, Rayne

    Read the article

  • Nginx + uWSGI + Django performance stuck on 100rq/s

    - by dancio
    I have configured Nginx with uWSGI and Django on CentOS 6 x64 (3.06GHz i3 540, 4GB), which should easily handle 2500 rq/s but when I run ab test ( ab -n 1000 -c 100 ) performance stops at 92 - 100 rq/s. Nginx: user nginx; worker_processes 2; events { worker_connections 2048; use epoll; } uWSGI: Emperor /usr/sbin/uwsgi --master --no-orphans --pythonpath /var/python --emperor /var/python/*/uwsgi.ini [uwsgi] socket = 127.0.0.2:3031 master = true processes = 5 env = DJANGO_SETTINGS_MODULE=x.settings env = HTTPS=on module = django.core.handlers.wsgi:WSGIHandler() disable-logging = true catch-exceptions = false post-buffering = 8192 harakiri = 30 harakiri-verbose = true vacuum = true listen = 500 optimize = 2 sysclt changes: # Increase TCP max buffer size setable using setsockopt() net.ipv4.tcp_rmem = 4096 87380 8388608 net.ipv4.tcp_wmem = 4096 87380 8388608 net.core.rmem_max = 8388608 net.core.wmem_max = 8388608 net.core.netdev_max_backlog = 5000 net.ipv4.tcp_max_syn_backlog = 5000 net.ipv4.tcp_window_scaling = 1 net.core.somaxconn = 2048 # Avoid a smurf attack net.ipv4.icmp_echo_ignore_broadcasts = 1 # Optimization for port usefor LBs # Increase system file descriptor limit fs.file-max = 65535 I did sysctl -p to enable changes. Idle server info: top - 13:34:58 up 102 days, 18:35, 1 user, load average: 0.00, 0.00, 0.00 Tasks: 118 total, 1 running, 117 sleeping, 0 stopped, 0 zombie Cpu(s): 0.0%us, 0.0%sy, 0.0%ni,100.0%id, 0.0%wa, 0.0%hi, 0.0%si, 0.0%st Mem: 3983068k total, 2125088k used, 1857980k free, 262528k buffers Swap: 2104504k total, 0k used, 2104504k free, 606996k cached free -m total used free shared buffers cached Mem: 3889 2075 1814 0 256 592 -/+ buffers/cache: 1226 2663 Swap: 2055 0 2055 **During the test:** top - 13:45:21 up 102 days, 18:46, 1 user, load average: 3.73, 1.51, 0.58 Tasks: 122 total, 8 running, 114 sleeping, 0 stopped, 0 zombie Cpu(s): 93.5%us, 5.2%sy, 0.0%ni, 0.2%id, 0.0%wa, 0.1%hi, 1.1%si, 0.0%st Mem: 3983068k total, 2127564k used, 1855504k free, 262580k buffers Swap: 2104504k total, 0k used, 2104504k free, 608760k cached free -m total used free shared buffers cached Mem: 3889 2125 1763 0 256 595 -/+ buffers/cache: 1274 2615 Swap: 2055 0 2055 iotop 30141 be/4 nginx 0.00 B/s 7.78 K/s 0.00 % 0.00 % nginx: wo~er process Where is the bottleneck ? Or what am I doing wrong ?

    Read the article

  • Best CPUs for speeding up compiling times of C++ w/ DistGCC

    - by Jay
    I'm putting together a distributed build farm with DistGCC to speed up our teams compile times and just looking for thoughts on which processors to use in the hosts. Are we going to get a noticeable decrease in time using 8 cores vs. 4-hyperthreaded cores? Big difference in time between i7 and Xeon? etc, etc. Just need advice from people who've put together kick-a build clusters. We've got a majority of the normal things to speed up builds in place (pre-compiled headers, ccache, local gigabit connections between them, tons of ram, etc) so please just give advice on the best processor to use. And money is a factor, but anythings doable if the performance increase is noticeable. Thanks. Jay EDIT: Although any advice IS welcome, please refrain from "Do this first" posts as we're not planning on skimping on things like SSD, maxed out RAM, etc. My personal system is a iMac Quad-core i5 with 8GB of RAM. When I build our project locally, my processor floats around 99-100% a majority of the time, which makes me assume it is a bottleneck, even if you made everything else faster. My ram on the other hand doesn't even get close to maxing out. It's also worth noting that I did research this, however every discussion I could find was primarily for gaming machines, which is obviously a different beast in usage. These machines won't even have monitors or anything but integrated graphics since they have one purpose: Build freakin fast. (hopefully)

    Read the article

  • Best CPUs for speeding up compiling times of C++ w/ DistGCC

    - by Jay
    I'm putting together a distributed build farm with DistGCC to speed up our teams compile times and just looking for thoughts on which processors to use in the hosts. Are we going to get a noticeable decrease in time using 8 cores vs. 4-hyperthreaded cores? Big difference in time between i7 and Xeon? etc, etc. Just need advice from people who've put together kick-a build clusters. We've got a majority of the normal things to speed up builds in place (pre-compiled headers, ccache, local gigabit connections between them, tons of ram, etc) so please just give advice on the best processor to use. And money is a factor, but anythings doable if the performance increase is noticeable. Thanks. Jay EDIT: Although any advice IS welcome, please refrain from "Do this first" posts as we're not planning on skimping on things like SSD, maxed out RAM, etc. My personal system is a iMac Quad-core i5 with 8GB of RAM. When I build our project locally, my processor floats around 99-100% a majority of the time, which makes me assume it is a bottleneck, even if you made everything else faster. My ram on the other hand doesn't even get close to maxing out. It's also worth noting that I did research this, however every discussion I could find was primarily for gaming machines, which is obviously a different beast in usage. These machines won't even have monitors or anything but integrated graphics since they have one purpose: Build freakin fast. (hopefully)

    Read the article

  • Best CPUs for speeding up compiling times of C++ w/ DistGCC

    - by Jay
    I'm putting together a distributed build farm with DistGCC to speed up our teams compile times and just looking for thoughts on which processors to use in the hosts. Are we going to get a noticeable decrease in time using 8 cores vs. 4-hyperthreaded cores? Big difference in time between i7 and Xeon? etc, etc. Just need advice from people who've put together kick-a build clusters. We've got a majority of the normal things to speed up builds in place (pre-compiled headers, ccache, local gigabit connections between them, tons of ram, etc) so please just give advice on the best processor to use. And money is a factor, but anythings doable if the performance increase is noticeable. Thanks. Jay EDIT: Although any advice IS welcome, please refrain from "Do this first" posts as we're not planning on skimping on things like SSD, maxed out RAM, etc. My personal system is a iMac Quad-core i5 with 8GB of RAM. When I build our project locally, my processor floats around 99-100% a majority of the time, which makes me assume it is a bottleneck, even if you made everything else faster. My ram on the other hand doesn't even get close to maxing out. It's also worth noting that I did research this, however every discussion I could find was primarily for gaming machines, which is obviously a different beast in usage. These machines won't even have monitors or anything but integrated graphics since they have one purpose: Build freakin fast. (hopefully)

    Read the article

  • Does fast typing influence fast programming?

    - by Lukasz Lew
    Many young programmers think that their bottleneck is typing speed. After some experience one realizes that it is not the case, you have to think much more than type. At some point my room-mate forced me to turn of the light (he sleeps during the night). I had to learn to touch type and I experienced an actual improvement in programming skill. The most surprising was that the improvement not due to sheer typing speed, but to a change in mindset. I'm less afraid now to try new things and refactor them later if they work well. It's like having a new tool in the bag. Have anyone of you had similar experience? Now I trained a touch typing a little with KTouch. I find auto-generate lessons the best. I can use this program to create new lessons out of text files but it's only verbatim training, not auto-generated based on a language model. Do you know any touch typing program that allows creation of custom, but randomized lessons?

    Read the article

  • Linux Experts Riddle: Network output of 10MB/s on 10GB/s NIC

    - by user150324
    I have two CentOS 6 servers. I am trying to transfer files between them. Source server has 10GB/s NIC nd destination server has 1GB/s NIC. Regardless to the command used nor the protocol, the transfer speed is ~1 Mega byte per second. The goal is at least couple dozens MB per second. I have tried: rsync (also with various encryptions), scp, wget, aftp, nc. Here's some testing results with iperf: [root@serv ~]# iperf -c XXX.XXX.XXX.XXX -i 1 ------------------------------------------------------------ Client connecting to XXX.XXX.XXX.XXX, TCP port 5001 TCP window size: 64.0 KByte (default) ------------------------------------------------------------ [ 3] local XXX.XXX.XXX.XXX port 33180 connected with XXX.XXX.XXX.XXX port 5001 [ ID] Interval Transfer Bandwidth [ 3] 0.0- 1.0 sec 1.30 MBytes 10.9 Mbits/sec [ ID] Interval Transfer Bandwidth [ 3] 1.0- 2.0 sec 1.28 MBytes 10.7 Mbits/sec [ ID] Interval Transfer Bandwidth [ 3] 2.0- 3.0 sec 1.34 MBytes 11.3 Mbits/sec [ ID] Interval Transfer Bandwidth [ 3] 3.0- 4.0 sec 1.53 MBytes 12.8 Mbits/sec [ ID] Interval Transfer Bandwidth [ 3] 4.0- 5.0 sec 1.65 MBytes 13.8 Mbits/sec [ ID] Interval Transfer Bandwidth [ 3] 5.0- 6.0 sec 1.79 MBytes 15.0 Mbits/sec [ ID] Interval Transfer Bandwidth [ 3] 6.0- 7.0 sec 1.95 MBytes 16.3 Mbits/sec [ ID] Interval Transfer Bandwidth [ 3] 7.0- 8.0 sec 1.98 MBytes 16.6 Mbits/sec [ ID] Interval Transfer Bandwidth [ 3] 8.0- 9.0 sec 1.91 MBytes 16.0 Mbits/sec [ ID] Interval Transfer Bandwidth [ 3] 9.0-10.0 sec 2.05 MBytes 17.2 Mbits/sec [ ID] Interval Transfer Bandwidth [ 3] 0.0-10.0 sec 1.68 MBytes 14.0 Mbits/sec I guess HD is not the bottleneck here.

    Read the article

  • Why are my socks proxies slow

    - by vps_newcomer
    I have a linux vps, and i have tried a few socks proxy setups to test their performance: All tests were using speedtest.net The standard ssh tunnel proxy 0.8mbit/s download and 0.1-0.2mbit/s upload speeds dante-server proxy 1.3mbit/s download and 0.4-0.5mbit/s upload I am wondering why are these speeds so slow? Is anything shaping them? Is it just the nature of socks proxies? I know that the ssh tunnel has to do encryption and what not so that is why its slow, but i was surprised to see that the second setup was also quite slow. On the VPS i have received download speeds of 25MB/s per second (thats about 200mbit/s and upload speed of atleast 5MB/s (haven't got a good enough pipe to test anything faster). The other option i was going to try is to setup OpenVPN and see how that goes, however i need to find a good tutorial as it's fairly complicated to setup. So why is it so slow? How can i test to see where the bottleneck is? How can i make it faster :D

    Read the article

  • What do you upgrade to make games load faster? [on hold]

    - by Superbest
    Let's say you have a relatively modern game like Shogun 2. The loading screens take several minutes. This bothers you and you'd like to improve it. What is actually going on when loading screens are up? I'm guessing assets are being loaded into memory from disk, and possibly being decompressed first. However, what is actually causing the slow down? The memory? Mainboard? CPU? HDD? If you had $100 to spend on upgrades and your only goal is to speed up loading screens without reducing other performance, what component of the computer does it make sense to upgrade for maximum benefit? If your answer is "it depends on the existing setup", what sort of benchmarks would you run to determine what is causing the bottleneck? What if you had $500 instead? I give the two budgets for context. I am not asking for actual recommendations about which component to buy (nor are the numbers supposed to be rigid limits), but what features are important when shopping for components with small and large budgets (a large budget could allow buying multiple components which are not so good on their own, but work particularly well together). I mention Shogun 2 as an example, but I'm asking about reducing overall loading times, across all games, not just one game. Therefore, "put it on a solid state disk" probably won't be good solution, because putting every game on your SDD will quickly fill it up.

    Read the article

  • Backup data rate on Raspberry Pi maxing out at 5 Mb/s. Why?

    - by bastibe
    I set up my Raspberry Pi as a Time Machine, as documented here. At the moment, the Raspberry Pi is connected to my MacBook Pro using a direct Ethernet cable. Also, an external hard drive (laptop drive) is connected to the Raspberry Pi using the USB port. However, backups are pretty slow. Activity Monitor claims that the Network is transferring a very steady 5 Mb/s, where my Time Capsule is transferring up to 8 Mb/s with a lot of fluctuation. The Raspberry Pi self-reports (top) that its CPU is only half-used, with about equal parts afpd, usb-storage and jbd2/sda1-8. Thus, I think that the processing power of the Raspberry Pi does not seem to be the problem here. To me, this looks like there is some kind of bottleneck that maxes out at 5 Mb/s thus potentially having my backups run at less than their potential speed. To the best of my knowledge, this might be the afp-daemon, the usb-bus or the external hard drive. So, my question is, how could I identify the true culprit and what can I do about it?

    Read the article

  • Server load high, CPU idle. NFS the cause?

    - by Mech Software
    I am running into a scenario where I'm seeing a high server load (sometimes upwards of 20 or 30) and a very low CPU usage (98% idle). I'm wondering if these wait states are coming as part of an NFS filesystem connection. Here is what I see in VMStat procs -----------memory---------- ---swap-- -----io---- --system-- -----cpu------ r b swpd free buff cache si so bi bo in cs us sy id wa st 2 1 0 1298784 0 0 0 0 16 5 0 9 1 1 97 2 0 0 1 0 1308016 0 0 0 0 0 0 0 3882 4 3 80 13 0 0 1 0 1307960 0 0 0 0 120 0 0 2960 0 0 88 12 0 0 1 0 1295868 0 0 0 0 4 0 0 4235 1 2 84 13 0 6 0 0 1292740 0 0 0 0 0 0 0 5003 1 1 98 0 0 4 0 0 1300860 0 0 0 0 0 120 0 11194 4 3 93 0 0 4 1 0 1304576 0 0 0 0 240 0 0 11259 4 3 88 6 0 3 1 0 1298952 0 0 0 0 0 0 0 9268 7 5 70 19 0 3 1 0 1303740 0 0 0 0 88 8 0 8088 4 3 81 13 0 5 0 0 1304052 0 0 0 0 0 0 0 6348 4 4 93 0 0 0 0 0 1307952 0 0 0 0 0 0 0 7366 5 4 91 0 0 0 0 0 1307744 0 0 0 0 0 0 0 3201 0 0 100 0 0 4 0 0 1294644 0 0 0 0 0 0 0 5514 1 2 97 0 0 3 0 0 1301272 0 0 0 0 0 0 0 11508 4 3 93 0 0 3 0 0 1307788 0 0 0 0 0 0 0 11822 5 3 92 0 0 From what I can tell when the IO goes up the waits go up. Could NFS be the cause here or should I be worried about something else? This is a VPS box on a fiber channel SAN. I'd think the bottleneck wouldn't be the SAN. Comments?

    Read the article

  • Why are my socks proxies slow

    - by vps_newcomer
    I have a linux vps, and i have tried a few socks proxy setups to test their performance: All tests were using speedtest.net The standard ssh tunnel proxy 0.8mbit/s download and 0.1-0.2mbit/s upload speeds dante-server proxy 1.3mbit/s download and 0.4-0.5mbit/s upload I am wondering why are these speeds so slow? Is anything shaping them? Is it just the nature of socks proxies? I know that the ssh tunnel has to do encryption and what not so that is why its slow, but i was surprised to see that the second setup was also quite slow. On the VPS i have received download speeds of 25MB/s per second (thats about 200mbit/s and upload speed of atleast 5MB/s (haven't got a good enough pipe to test anything faster). The other option i was going to try is to setup OpenVPN and see how that goes, however i need to find a good tutorial as it's fairly complicated to setup. So why is it so slow? How can i test to see where the bottleneck is? How can i make it faster :D

    Read the article

  • Poor SSL performance with vsftpd

    - by petrus
    I'm trying to tweak vsftpd to achieve maximum performance for my usage: I have only one or two clients that connect to the server. File size is between ~15MB and 1GB. Typical transfer batch represent between 1 and 2GB of data. For testing purposes, I'm using a tmpfs on both sides (thus eliminating any disks bottleneck) with a single 1GB file. When SSL is disabled, performance is good, with a transfer rate at ~120MB/s (reaching the limits of gigabit networking). With SSL enabled only for control traffic (and not data traffic), performance drops at about 112MB/s, which is still within the acceptable limits. However, when SSL is enabled for data flows, the transfer speed drops dramatically: 6.7MB/s using 3DES & SHA (ssl_ciphers=DES-CBC3-SHA in vsftpd.conf) 16MB/s using DES & SHA (ssl_ciphers=DES-CBC-SHA) I didn't tested other ciphers, but from what I can see from the CPU usage during the transfer, it seems that vsftpd is only using a single cpu/core per client. While this can fit for large ftp sites with hundreds of clients, I'd like to avoid this behavior and use more ressources on the server. On a side note, if you have any ideas regarding other openssl ciphers...

    Read the article

  • Unexplained cache RAM drops on Linux machine

    - by FunkyChicken
    I run a CentOS 5.7 64 machine with 24gb ram and running kernel 2.6.18-274.12.1.el5. This machine runs only Nginx, php-fpm and Xcache as extra applications. Since about 3 weeks my memory behavior on this machine has changed and I cannot explain why. There are no crons running which flush anything like this. There are also no large numbers of files being deleted/changed during these drops. The 'cached' memory gets dropped about every few hours, but it's never a set gap between flushes, this indicates to me that some bottleneck gets reached instead. It also always seems to be when total memory usages gets to about 18GB, but again, not always exactly 18GB. This is a graph of my memory usage: As you can see in the graph the 'buffers' always stay more or less the same, it is mainly the 'cache' that gets dropped. Running vmstat -m I have outputted the memory usage just before and just after a memory drop. The output is here: http://pastebin.com/diff.php?i=hJqZqztm 'old version' being before, 'new version' being after a drop. About 3 weeks ago my server crashed during a heavy DDOS attack, after I rebooted the machine this odd behavior started. I have checked a bunch of logs, restarted the machine again, and cannot find any indication what changed. During these 'cache' memory drops, my iNode usage drops at the same time. Does anyone have any idea what might be causing this behavior? Clearly my RAM isn't full, so I am curious why this could be happening.

    Read the article

  • Should I partition a 1TB Hard Disk whose primary use is media storage?

    - by Senthil
    I am going to get a 1TB hard disk. I will be storing 1080p or 720p movies, high-bitrate music and pictures in it. I use my PC 90% of the time only to play/listen/see those. I am running out of space in my current HD so I am getting another one. My specs are 2.7GHz Dual Core, 512MB GeForce 9400GT, 2GB DDR2 RAM and all the proper matroska codecs/players. I guess that is enough to play 1080p movies withough a glitch, given an ideal hard disk. I've read about proper partitioning giving performance improvement etc.. I don't want my hard disk to be the bottleneck. Can someone tell me whether I should partition my 1TB hard disk into many drives? If I should, what is the ideal size of each partition? Smooth playing of movies is very important to me. Once I start filling up the disk, there is no turning back. So I want to get it right before I start. Thanks.

    Read the article

  • Cluster FIle System

    - by Ben
    We are looking for to choose a clustered file system for our in house appplication. Let me first highlight my requirement. we have a storage and 2 servers at present.We get the data files from remote servers to our server and on both servers we are running our application to access those data and make a final result as per our requirements. In future may be after 3-4 months, we can add another servers in current cluster pool to handle more data load from remote location data senders. So my requirement is that to integrate same storage partition on 2-3 servers , it might be 4-5 more servers in future, My application read data from storage partition and write back to storage partition. Is there any bottleneck / limitation from RHCS , GFS2 or anything.? We are new with RHCS + GFS and all. Can we have any other better approach or someway to deal with our requirement light way? what is the best OS version for this ? how's RHEL 6.4 64 bit ? please share some case study or some gudie reference as per past experiences with such environnmnets Regards, Ben

    Read the article

< Previous Page | 7 8 9 10 11 12 13 14 15 16 17  | Next Page >