I'm using RISC-V I would like to customize the number of cores in a tile.
Which chisel file should I modify?
Are you using RocketChip generator?
If you want to create several cores, you can change the number of cores in "rocket-chip/src/main/scala/uncore/Builder.scala" NTiles param.
If you want to add it inside a Tile, maybe you should modify rocket.scala and tile.scala, but take into account that they will share the L1 cachés and that could create conflicts.
Related
I am using the MSIX manager tool to convert a *.msix (an application installer) to a *.vhdx so that it can be mounted in an Azure virtual machine. One of the flags that the tool requires is -vhdSize, which is in megabytes. This has proven to be problematic because I have to guess what the size should be based off the MSIX. I have ran into numerous creation errors due to too small of a vhdSize.
I could set it to an arbitrarily high value in order to get around these failures, but that is not ideal. Alternatively, guessing the correct size is an imprecise science and a chore to do repeatedly.
Is there a way to have the tool dynamically set the vhdSize, or am I stuck guessing a value that is both large enough to accommodate the file, but not too large as to waste disk space? Or, is there a better way to create a *.vhdx file?
https://techcommunity.microsoft.com/t5/windows-virtual-desktop/simplify-msix-image-creation-with-the-msixmgr-tool/m-p/2118585
There is an MSIX Hero app that could select a size for you, it will automatically check how big the uncompressed files are, add an extra buffer for safety (currently double the original size), and round it to the next 10MB. Reference from https://msixhero.net/documentation/creating-vhd-for-msix-app-attach/
How does one use RedHawk and distribute components to different nodes? If the two processors are the same (eg x86_64) the implementation section of the spd would have only one implementation section. How do I force a component to one of two or more nodes? Or do I add additional implementation sections? Is there an option in the IDE that I do not see to set all this up or do I have to add allocation properties manually to force this?
There are three ways to have a component spill over onto another executable device (GPP). First, if there are two GPPs available in your domain, components will spill over to the second GPP when resources are fully allocated on the first GPP. Second, you can use the device assignment sequence when creating your application, per section 9.3.3.2 of the REDHAWK User Guide. Lastly, you can add or change one of the allocation properties on one of the devices and have your components look specifically for that allocation property.
Is there a good, graphical way to represent disk usage changes in a linux/unix filesystem over time?
Let me elaborate: there are several good ways to represent disk usage in a filesystem. I'm not interested in summary statistics such total space used (as given by du(1)), but more advanced interactive/visualization tools such as ncdu, gdmap, filelight or baobab, that can give me an idea of where the space is being used.
From a technical perspective, I think the best approach is squarified tree-maps (as available in gdmap), since it makes a better use of the visual space available. The circular approach used by filelight for instance cannot represent huge hierarchies efficiently, and it's dubious how to account for the increasing area of the outer rings in the representation from a human perspective. Looks nice, but that's about it.
Treemaps are perfect to have the current snapshot of disk usage in the filesystem, but I'd like to have something similar to see how disk usage has been evolving over time.
My current solution is very simple: I'm dumping the filesystem usage state using "ncdu -o" over time, and then I compare them side-by-side using two ncdu instances. It's very inefficient, but does the job. I'd like something more visual though.
All the relevant information can be dumped using:
find [dir] -printf "%P\t%s\n"
I did a crappy hack to load this state information in gdmap, so I can use two gdmap instances instead. Still not optimal though, as a treemap will fit the total allocated space into the same rectangle. As such, you cannot really tell if the same area is equivalent to more or less space. If two big directories grow proportionately, they will not change the visualization.
I need something better than that. Obviously, I cannot plot the cumulative directory sizes in a simple line plot, as I would have too many directories.
I'd like something similar to a treemap, where maybe the color of the square represents size increase/decrease using some colormap. However, since a treemap will show individual files as opposed to directories, it's not obvious on how to color-map a directory in which the allocated space has been growing/shrinking due to new/removed files.
What kind of visualization techniques could be used to see the evolution of allocated space over time, which take the whole underlying tree into account?
To elaborate even more, in a squarified treemap the whole allocated space is proportionally divided by file size, and each directory logically clusters the allocated space within it. As such, we don't "see" directories, we see the proportional space taken by it's content.
How we could extend and/or improve the visualization in order to see how the allocated space has been moved to a different area of the treemap?
You can usee Cacti for this.
You need to install snmp deamon on you machine and install cacti (freeware) localy or on any other PC and monitor you linux machine.
http://blog.securactive.net/wp-content/uploads/2012/12/cacti_performance_vision1.png
You can monitor network interfaces, spaces of any partitions and lot of other parameters of your LINUX OS.
apt-get install cacti
vim /etc/snmp/snmpd.conf
add this at about 42 line:
view systemonly included .1.3.6.1
close and restart snmpd deamon
go to cacti config and try to discover your linux machine.
Hi I've looked online but I can't seem to find the answer whether I need to do anything to make matlab use all cores? From what I understand multi-threading has been supported since 2007. On my machine matlab only uses one core #100% and the rest hang at ~2%. I'm using a 64 bit Linux (Mint 12). On my other computer which has only 2 cores and is 32 bit Matlab seems to be utilizing both cores #100%. Not all of the time but in sufficient number of cases. On the 64 bit, 4 core PC this never happens.
Do I have to do anything in 64 bit to get Matlab to use all the cores whenever possible? I had to do some custom linking after install as Matlab wasn't finding the libraries (eg. libc.so.6) because it wasn't looking in the correct places.
By standard, since the latest release, you can use 12 cores using the Parallel Computing Toolbox. Without this toolbox, I guess you're out of luck. Any additional cores could be accessed by the MATLAB Distributed Computing Server, where you actually pay per number of worker threads.
To make matlab use your multiple cores you have to do
matlabpool open
And it of course works better if you actually have multithreaded code (like using the spmd function or parfor loops)
More info at the Matlab homepage
MATLAB has only one single thread for Computation.
That said, multiple threads would be created for certain functions which use the multithreaded features of the BLAS libraries that it uses underneath.
Thus, you would only be able to gain a 'multi threaded' advantage if you are calling functions which use these multi-threaded blas libraries.
This link has information on the list of functions which are multithreaded.
Now for the use of your cores, that would depend on your OS. I believe the OS would have to load balance your threads to be used on all cores. One CANNOT set affinities to threads from within MATLAB. One can however set worker MATLAB processes to have affinities to cores from within the Parallel Computing toolbox.
However, you could always try setting the affinity for the MATLAB process to all your processors manually by the details available at the following link for Linux
Windows users can simply right click on the process in the task manager and set affinity.
My understanding is that this is only a request to the OS and is not a hard binding rule that the OS must adhere to.
I am trying to profile my software (in Linux) with oprofile. My software consists of both userspace and kernel module. First my doubt is what does the --separate=kernel option do? What will be the difference when running without that option? I did try to see it but couldn't find any difference. Could you please post an example?
Can't i profile a kernel module without the --seperate=kernel option?
Thanks,
Bala
In oprofile when used with option --seperate=kernel, it seperates the kernel and kernel modules per application.
--seperate='library' seperates the samples for the dynamically linked object per application basis.
kernel, dynamically linked object are just not specific to the application we want to profile alone. But at the same time our application spends considerable amount of time in them.
So --seperate allows one to get the samples from the point of view of the application we are interested in profiling. It can also give samples based on individual threads also.
Kernel can be profiled by providing --vmlinux option to opcontrol.
Ex:- opcontrol --vmlinux=/boot/vmlinux-2.6.27.23-0.1-preempt
--seperate is additional option that allows us to see the samples at different resolutions.