A possible cause of a CL_OUT_OF_RESOURCES error is that the card is being used to run a display (Ref). I have found, however, that I continue to get this error after disconnecting the display and it persists until I restart. Is there a command that will make the OpenCL resources available again?
CL_OUT_OF_RESOURCES is a common error to nVIDIA driver. And can be caused by:
Real out of resources (rare)
Reading an array that was used by a kernel that read/writed out of bounds. (typical)
Any other strange error that does not have an appropriate error code.
You are provably facing the second one, so, I would check the kernels.
EDIT: As you said that it happens until restart. Maybe you can check if you are deleting properly all the OpenCL objects. Events are very tricky and easy to leak some OpenCL memory.
How much memory are you trying to allocate, and how much does the card have on board? A video card driving a display has a certain amount of memory set aside for some operations. The driver may simply be reserving this memory and not caring if the display is gone till it is restarted.
On that note, it is possible to restart the video driver in Windows using devcon. On Linux, you could try an
lsmod | grep nvidia
and once you know the module name, perhaps an
rmmod
or
modprobe -r
I don't know if this will work on OSX.
Back in the good old/bad old days when I developed on VAX/VMS it had a feature called 'Installed Shared Images' whereby if one expected one's executable program would be run by many users concurrently one could invoke the INSTALL utility thus:
$ INSTALL
INSTALL> ADD ONES_PROGRAM.EXE/SHARE
INSTALL> EXIT
The /SHARE flag had the effect of separating out the code from the data so that concurrent users of ONES_PROGRAM.EXE would all share the code (on a read-only basis of course) but each would have their own copy of the data (on a read-write basis). This technique/feature saved Mbytes of memory (which was necessary in those days) as only ONE copy of the program's code ever needed to be resident in VAX memory irrespective of the number of concurrent users.
Does Windows XP have something similar? I can't figure out if the Control Panel's 'Add Programs/Features' is the equivalent (I think it is, but I'm not sure)
Many thanks for any info
Richard
p.s. INSTALL would also share Libraries as well as Programs in case you were curious
The Windows virtual memory manager will do this automatically for you. So long as the module can be loaded at the same address in each process, the physical memory for the code will be shared between each process that loads that module. That is true for all modules, libraries as well as executables.
This is achieved by the linker marking code segments as being shareable. So, linkers mark code segments as being shareable, and data segments otherwise.
The bottom line is that you do not have to do anything explicit to make this happen.
At work we are using some pretty powerful machines: HP Z600 with dual xeon #2.5GHz, 8-16GB ram. Unfortunately due to ill-fitting company policies we are forced to use 32-bit XP, so I made a PAE ramdrive out of the unused 4GB RAM.
Now, the temporary files are on the ramdrive. I've also tried moving the whole project to the ramdrive, then to an SSD, but there was no noticeable improvement in hosted-mode startup or compilation times.
I've then run SysInternals' Process Monitor to see if there are any bottlenecks that are not visible with task manager / hard-disk activity led, but I have not seen anything notable - except some buffer overflows which I don't understand what they mean.
I can assume that performance for OOMPH startup and GWT compilation are tied so I'm using the compilation times as benchmarking between various changes.
I've activated and deactivated hyper-threading and turbo-boost in BIOS, but again saw no differences. Hyperthreading even seems to make everything slower, I can assume that context switching penalty is higher for 16 cores than for 8 cores. Turbo-boost does not seem to do anything, I can assume it only works under Win7, I have not succeeded in activating the driver. It should boost the core from 2.5Ghz to 2.8Ghz.
Deactivated indexing and timestamping on NTFS drives, changed the performance setting from foreground to background and back, used another instance of Eclipse - no changes.
For compilation I've tried specifying a different number of workers, larger memory and some other options. Everything above two workers increases compilation time.
Older HP machines (XW6600) seem to compile a bit faster, perhaps because of the 2.8GHz clock, but their hosted mode seems to start up slower.
To sum up, memory usage is at about 2.6GB, pagefile usage is zero, harddrive is not signaling much activity, CPU activity is <10% (single core at about 50-70%) but still the computer seems to do nothing for some time while compiling or launching OOMPH GWT.
Ok, so now that I've tried everything I knew and found on the Internet, is there anything else that I can try? Will switching to 64-bit Win7 improve much (this is due next year anyway)? Are there any hardware/software options that I can tweak?
L.E.: also ran RATT (tracer from MS) to see if there are any interrupts taking too long, but everything seems in order. Antivirus does not make a difference. Benchmarked another GWT project against my i7 mobile (2630q) and the i7 is about 70% faster, though it has about the same clock.
In most cases I've encountered the reason for slow compilation/hosted mode refresh is that application is written this way.
For compilation there are few things to watch out for:
Don't keep unused classes and modules in your classpath, remove them if possible because GWT is parsing them anyway at precompile stage
whatch out for GWT-RPC type explosion, this is usually a cause of all problems
Be really carefull with interface ContextWithLokup, always try to minimize the number of methods used in interface which extends ContextWithLookup
Try to check out some other compilation options, like distributed compilation , soft permutations or multi-jvm compilation (run compiler with system property -Dgwt.jjs.permutationWorkerFactory=com.google.gwt.dev.ExternalPermutationWorkerFactory and -localWorkers to specify number of JVMs)
For hosted mode:
Use lazy loading where it is possible. The greatest problem with hosted mode i saw, i that application is trying to initialize too many classes which aren't even used on current screen, this can greatly speedup a hosted mode startup. Again, stuff like RPC type explosion affects hosted mode as well
That's all I can advise. Stuff like ram disk can speed up stuff like -compileReport, since it can generate a huge number of files.
I know this is not so much a programming question but it is relevant.
I work on a fairly large cross platform project. On Windows I use VC++ 2008. On Linux I use gcc. There are around 40k files in the project. Windows is 10x to 40x slower than Linux at compiling and linking the same project. How can I fix that?
A single change incremental build 20 seconds on Linux and > 3 mins on Windows. Why? I can even install the 'gold' linker in Linux and get that time down to 7 seconds.
Similarly git is 10x to 40x faster on Linux than Windows.
In the git case it's possible git is not using Windows in the optimal way but VC++? You'd think Microsoft would want to make their own developers as productive as possible and faster compilation would go a long way toward that. Maybe they are trying to encourage developers into C#?
As simple test, find a folder with lots of subfolders and do a simple
dir /s > c:\list.txt
on Windows. Do it twice and time the second run so it runs from the cache. Copy the files to Linux and do the equivalent 2 runs and time the second run.
ls -R > /tmp/list.txt
I have 2 workstations with the exact same specs. HP Z600s with 12gig of ram, 8 cores at 3.0ghz. On a folder with ~400k files Windows takes 40seconds, Linux takes < 1 second.
Is there a registry setting I can set to speed up Windows? What gives?
A few slightly relevant links, relevant to compile times, not necessarily i/o.
Apparently there's an issue in Windows 10 (not in Windows 7) that closing a process holds a global lock. When compiling with multiple cores and therefore multiple processes this issue hits.
The /analyse option can adversely affect perf because it loads a web browser. (Not relevant here but good to know)
Unless a hardcore Windows systems hacker comes along, you're not going to get more than partisan comments (which I won't do) and speculation (which is what I'm going to try).
File system - You should try the same operations (including the dir) on the same filesystem. I came across this which benchmarks a few filesystems for various parameters.
Caching. I once tried to run a compilation on Linux on a RAM disk and found that it was slower than running it on disk thanks to the way the kernel takes care of caching. This is a solid selling point for Linux and might be the reason why the performance is so different.
Bad dependency specifications on Windows. Maybe the chromium dependency specifications for Windows are not as correct as for Linux. This might result in unnecessary compilations when you make a small change. You might be able to validate this using the same compiler toolchain on Windows.
A few ideas:
Disable 8.3 names. This can be a big factor on drives with a large number of files and a relatively small number of folders: fsutil behavior set disable8dot3 1
Use more folders. In my experience, NTFS starts to slow down with more than about 1000 files per folder.
Enable parallel builds with MSBuild; just add the "/m" switch, and it will automatically start one copy of MSBuild per CPU core.
Put your files on an SSD -- helps hugely for random I/O.
If your average file size is much greater than 4KB, consider rebuilding the filesystem with a larger cluster size that corresponds roughly to your average file size.
Make sure the files have been defragmented. Fragmented files cause lots of disk seeks, which can cost you a factor of 40+ in throughput. Use the "contig" utility from sysinternals, or the built-in Windows defragmenter.
If your average file size is small, and the partition you're on is relatively full, it's possible that you are running with a fragmented MFT, which is bad for performance. Also, files smaller than 1K are stored directly in the MFT. The "contig" utility mentioned above can help, or you may need to increase the MFT size. The following command will double it, to 25% of the volume: fsutil behavior set mftzone 2 Change the last number to 3 or 4 to increase the size by additional 12.5% increments. After running the command, reboot and then create the filesystem.
Disable last access time: fsutil behavior set disablelastaccess 1
Disable the indexing service
Disable your anti-virus and anti-spyware software, or at least set the relevant folders to be ignored.
Put your files on a different physical drive from the OS and the paging file. Using a separate physical drive allows Windows to use parallel I/Os to both drives.
Have a look at your compiler flags. The Windows C++ compiler has a ton of options; make sure you're only using the ones you really need.
Try increasing the amount of memory the OS uses for paged-pool buffers (make sure you have enough RAM first): fsutil behavior set memoryusage 2
Check the Windows error log to make sure you aren't experiencing occasional disk errors.
Have a look at Physical Disk related performance counters to see how busy your disks are. High queue lengths or long times per transfer are bad signs.
The first 30% of disk partitions is much faster than the rest of the disk in terms of raw transfer time. Narrower partitions also help minimize seek times.
Are you using RAID? If so, you may need to optimize your choice of RAID type (RAID-5 is bad for write-heavy operations like compiling)
Disable any services that you don't need
Defragment folders: copy all files to another drive (just the files), delete the original files, copy all folders to another drive (just the empty folders), then delete the original folders, defragment the original drive, copy the folder structure back first, then copy the files. When Windows builds large folders one file at a time, the folders end up being fragmented and slow. ("contig" should help here, too)
If you are I/O bound and have CPU cycles to spare, try turning disk compression ON. It can provide some significant speedups for highly compressible files (like source code), with some cost in CPU.
NTFS saves file access time everytime. You can try disabling it:
"fsutil behavior set disablelastaccess 1"
(restart)
The issue with visual c++ is, as far I can tell, that it is not a priority for the compiler team to optimize this scenario.
Their solution is that you use their precompiled header feature. This is what windows specific projects have done. It is not portable, but it works.
Furthermore, on windows you typically have virus scanners, as well as system restore and search tools that can ruin your build times completely if they monitor your buid folder for you. windows 7 resouce monitor can help you spot it.
I have a reply here with some further tips for optimizing vc++ build times if you're really interested.
The difficulty in doing that is due to the fact that C++ tends to spread itself and the compilation process over many small, individual, files. That's something Linux is good at and Windows is not. If you want to make a really fast C++ compiler for Windows, try to keep everything in RAM and touch the filesystem as little as possible.
That's also how you'll make a faster Linux C++ compile chain, but it is less important in Linux because the file system is already doing a lot of that tuning for you.
The reason for this is due to Unix culture:
Historically file system performance has been a much higher priority in the Unix world than in Windows. Not to say that it hasn't been a priority in Windows, just that in Unix it has been a higher priority.
Access to source code.
You can't change what you can't control. Lack of access to Windows NTFS source code means that most efforts to improve performance have been though hardware improvements. That is, if performance is slow, you work around the problem by improving the hardware: the bus, the storage medium, and so on. You can only do so much if you have to work around the problem, not fix it.
Access to Unix source code (even before open source) was more widespread. Therefore, if you wanted to improve performance you would address it in software first (cheaper and easier) and hardware second.
As a result, there are many people in the world that got their PhDs by studying the Unix file system and finding novel ways to improve performance.
Unix tends towards many small files; Windows tends towards a few (or a single) big file.
Unix applications tend to deal with many small files. Think of a software development environment: many small source files, each with their own purpose. The final stage (linking) does create one big file but that is an small percentage.
As a result, Unix has highly optimized system calls for opening and closing files, scanning directories, and so on. The history of Unix research papers spans decades of file system optimizations that put a lot of thought into improving directory access (lookups and full-directory scans), initial file opening, and so on.
Windows applications tend to open one big file, hold it open for a long time, close it when done. Think of MS-Word. msword.exe (or whatever) opens the file once and appends for hours, updates internal blocks, and so on. The value of optimizing the opening of the file would be wasted time.
The history of Windows benchmarking and optimization has been on how fast one can read or write long files. That's what gets optimized.
Sadly software development has trended towards the first situation. Heck, the best word processing system for Unix (TeX/LaTeX) encourages you to put each chapter in a different file and #include them all together.
Unix is focused on high performance; Windows is focused on user experience
Unix started in the server room: no user interface. The only thing users see is speed. Therefore, speed is a priority.
Windows started on the desktop: Users only care about what they see, and they see the UI. Therefore, more energy is spent on improving the UI than performance.
The Windows ecosystem depends on planned obsolescence. Why optimize software when new hardware is just a year or two away?
I don't believe in conspiracy theories but if I did, I would point out that in the Windows culture there are fewer incentives to improve performance. Windows business models depends on people buying new machines like clockwork. (That's why the stock price of thousands of companies is affected if MS ships an operating system late or if Intel misses a chip release date.). This means that there is an incentive to solve performance problems by telling people to buy new hardware; not by improving the real problem: slow operating systems. Unix comes from academia where the budget is tight and you can get your PhD by inventing a new way to make file systems faster; rarely does someone in academia get points for solving a problem by issuing a purchase order. In Windows there is no conspiracy to keep software slow but the entire ecosystem depends on planned obsolescence.
Also, as Unix is open source (even when it wasn't, everyone had access to the source) any bored PhD student can read the code and become famous by making it better. That doesn't happen in Windows (MS does have a program that gives academics access to Windows source code, it is rarely taken advantage of). Look at this selection of Unix-related performance papers: http://www.eecs.harvard.edu/margo/papers/ or look up the history of papers by Osterhaus, Henry Spencer, or others. Heck, one of the biggest (and most enjoyable to watch) debates in Unix history was the back and forth between Osterhaus and Selzer http://www.eecs.harvard.edu/margo/papers/usenix95-lfs/supplement/rebuttal.html
You don't see that kind of thing happening in the Windows world. You might see vendors one-uping each other, but that seems to be much more rare lately since the innovation seems to all be at the standards body level.
That's how I see it.
Update: If you look at the new compiler chains that are coming out of Microsoft, you'll be very optimistic because much of what they are doing makes it easier to keep the entire toolchain in RAM and repeating less work. Very impressive stuff.
I personally found running a windows virtual machine on linux managed to remove a great deal of the IO slowness in windows, likely because the linux vm was doing lots of caching that Windows itself was not.
Doing that I was able to speed up compile times of a large (250Kloc) C++ project I was working on from something like 15 minutes to about 6 minutes.
Incremental linking
If the VC 2008 solution is set up as multiple projects with .lib outputs, you need to set "Use Library Dependency Inputs"; this makes the linker link directly against the .obj files rather than the .lib. (And actually makes it incrementally link.)
Directory traversal performance
It's a bit unfair to compare directory crawling on the original machine with crawling a newly created directory with the same files on another machine. If you want an equivalent test, you should probably make another copy of the directory on the source machine. (It may still be slow, but that could be due to any number of things: disk fragmentation, short file names, background services, etc.) Although I think the perf issues for dir /s have more to do with writing the output than measuring actual file traversal performance. Even dir /s /b > nul is slow on my machine with a huge directory.
I'm pretty sure it's related to the filesystem. I work on a cross-platform project for Linux and Windows where all the code is common except for where platform-dependent code is absolutely necessary. We use Mercurial, not git, so the "Linuxness" of git doesn't apply. Pulling in changes from the central repository takes forever on Windows compared to Linux, but I do have to say that our Windows 7 machines do a lot better than the Windows XP ones. Compiling the code after that is even worse on VS 2008. It's not just hg; CMake runs a lot slower on Windows as well, and both of these tools use the file system more than anything else.
The problem is so bad that most of our developers that work in a Windows environment don't even bother doing incremental builds anymore - they find that doing a unity build instead is faster.
Incidentally, if you want to dramatically decrease compilation speed in Windows, I'd suggest the aforementioned unity build. It's a pain to implement correctly in the build system (I did it for our team in CMake), but once done automagically speeds things up for our continuous integration servers. Depending on how many binaries your build system is spitting out, you can get 1 to 2 orders of magnitude improvement. Your mileage may vary. In our case I think it sped up the Linux builds threefold and the Windows one by about a factor of 10, but we have a lot of shared libraries and executables (which decreases the advantages of a unity build).
How do you build your large cross platform project?
If you are using common makefiles for Linux and Windows you could easily degrade windows performance by a factor of 10 if the makefiles are not designed to be fast on Windows.
I just fixed some makefiles of a cross platform project using common (GNU) makefiles for Linux and Windows. Make is starting a sh.exe process for each line of a recipe causing the performance difference between Windows and Linux!
According to the GNU make documentation
.ONESHELL:
should solve the issue, but this feature is (currently) not supported for Windows make. So rewriting the recipes to be on single logical lines (e.g. by adding ;\ or \ at the end of the current editor lines) worked very well!
IMHO this is all about disk I/O performance. The order of magnitude suggests a lot of the operations go to disk under Windows whereas they're handled in memory under Linux, i.e. Linux is caching better. Your best option under windows will be to move your files onto a fast disk, server or filesystem. Consider buying an Solid State Drive or moving your files to a ramdisk or fast NFS server.
I ran the directory traversal tests and the results are very close to the compilation times reported, suggesting this has nothing to do with CPU processing times or compiler/linker algorithms at all.
Measured times as suggested above traversing the chromium directory tree:
Windows Home Premium 7 (8GB Ram) on NTFS: 32 seconds
Ubuntu 11.04 Linux (2GB Ram) on NTFS: 10 seconds
Ubuntu 11.04 Linux (2GB Ram) on ext4: 0.6 seconds
For the tests I pulled the chromium sources (both under win/linux)
git clone http://github.com/chromium/chromium.git
cd chromium
git checkout remotes/origin/trunk
To measure the time I ran
ls -lR > ../list.txt ; time ls -lR > ../list.txt # bash
dir -Recurse > ../list.txt ; (measure-command { dir -Recurse > ../list.txt }).TotalSeconds #Powershell
I did turn off access timestamps, my virus scanner and increased the cache manager settings under windows (>2Gb RAM) - all without any noticeable improvements. Fact of the matter is, out of the box Linux performed 50x better than Windows with a quarter of the RAM.
For anybody who wants to contend that the numbers wrong - for whatever reason - please give it a try and post your findings.
Try using jom instead of nmake
Get it here:
https://github.com/qt-labs/jom
The fact is that nmake is using only one of your cores, jom is a clone of nmake that make uses of multicore processors.
GNU make do that out-of-the-box thanks to the -j option, that might be a reason of its speed vs the Microsoft nmake.
jom works by executing in parallel different make commands on different processors/cores.
Try yourself an feel the difference!
I want to add just one observation using Gnu make and other tools from MinGW tools on Windows: They seem to resolve hostnames even when the tools can not even communicate via IP. I would guess this is caused by some initialisation routine of the MinGW runtime. Running a local DNS proxy helped me to improve the compilation speed with these tools.
Before I got a big headache because the build speed dropped by a factor of 10 or so when I opened a VPN connection in parallel. In this case all these DNS lookups went through the VPN.
This observation might also apply to other build tools, not only MinGW based and it could have changed on the latest MinGW version meanwhile.
I recently could archive an other way to speed up compilation by about 10% on Windows using Gnu make by replacing the mingw bash.exe with the version from win-bash
(The win-bash is not very comfortable regarding interactive editing.)
Anyone know likely avenues of investigation for kernel launch failures that disappear when run under cuda-gdb? Memory assignments are within spec, launches fail on the same run of the same kernel every time, and (so far) it hasn't failed within the debugger.
Oh Great SO Gurus, What now?
cuda-gdb spills all shared memory and registers to local memory. So when something runs ok built for debugging and fails otherwise, it usually means out of bounds shared memory access. cuda-memcheck might help, depending on what sort of card you are using. Fermi is better than older cards in that respect.
EDIT:
Casting my mind back to the bad old days, I remember having an ornery GT9500 which used to throw similar NV13 errors and have random code failures when running very memory intensive kernels with a lot of shared memory activity. Never when debugging. I put it down to bad hardware and moved on to a GT200, never to see a similar error since. One possibility might be bad hardware. Is this a G92 (9800GT or similar)?
CUDA GDB can make some of the cuda operations synchronous.
Are you reading from a memory after has been initialized ?
are you using Streams?
Are you launching more than one kernel?
Where and how does it fail ?