My client uses HDF5 extensively via MetLab but would like to write an
application in C#/.net. I am new HDF5 but a very versed C# programmer. I
am not finding much documentation on the dotnet wrapper. Can anyone point
me to some resources that may help?
Is there a way to reshape an array with HDFView? I have an array that is
stored as a 1D array but in reality it can be interpreted as a 2D Image. So I
would like to be able to open the data array as an image in HDFView but
somehow tell the dialog box to convert the array from a 1D to a 2D
Not possible with the default implementation.
You could extend DefaultImageView.java to map a 1D array to an 2D
image.
Thanks
--pc
On 4/8/2013 1:23 PM, Michael Jackson wrote:
Is there a way to reshape an array with HDFView? I have an array that is stored as a 1D
array but in reality it can
On Fri, Apr 05, 2013 at 12:16:03PM -0500, Charles Henderson wrote:
My client uses HDF5 extensively via MetLab but would like to write an
application in C#/.net. I am new HDF5 but a very versed C# programmer. I
am not finding much documentation on the dotnet wrapper. Can anyone point
me to
wow, you find out this.
We registered the domain name for our C# and Powershell project.
Gerd (our application architect) and his wife made the PSH5X movie .
Thanks
--pc
On 4/8/2013 4:06 PM, Rob Latham wrote:
On Fri, Apr 05, 2013 at 12:16:03PM -0500, Charles Henderson wrote:
My client uses
Hi,
I have a question regarding the performance of parallel I/O vs MPI
communication based calls. I have data which needs to be accessed by
different processors. If the data is in memory then MPI calls (Send/Recv)
does the job. In an another scenario the data is written to a H5 file and
Hi Mark,
Thank you for answering my question. You are right about the
practicality issue. This isn't a serious issue if the data is stored in a
distributed sense with some indicators specifying which processor has the
data. This data is treated as a background database and it doesn't move
Hi Suman,
I think you are hinting at the fact that unstructured data is harder to manage
with true concurrent parallel I/O to a single, shared file, right? Yeah, it is.
Honestly, I don't have much experience with that. My impression has always been
that the more information you can give HDF5
Thanks a lot Mark. Collective communication may not always be possible as
two processors may access to the same data. Are you suggesting that one
needs to separate I/O requests into collective and independent modes? Can
one do a collective I/O even when the data is non-contiguous?
Regards
Suman
Thanks a lot Mark. Collective communication may not always be possible as two
processors may access to the same data. Are you suggesting that one needs to
separate I/O requests into collective and independent modes?
Yes, I guess I am. I mean, if its practical to do so.
Can one do a
Thanks once again for the advice.
Regards
Suman
On Tue, Apr 9, 2013 at 11:23 AM, Miller, Mark C. mille...@llnl.gov wrote:
Thanks a lot Mark. Collective communication may not always be possible
as two processors may access to the same data. Are you suggesting that one
needs to separate
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