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From Matthias Boehm <mboe...@gmail.com>
Subject Re: distributed cholesky on systemml
Date Sun, 22 Apr 2018 01:59:58 GMT
thanks for catching this - I just ran a toy example and this seems to
be a rewrite issue (there are specific right indexing rewrites that
collapse U[1:k,1:k] and U[1:k,k+1:n] into a single access to U which
helps for large distributed matrices). As a workaround, you can set
"sysml.optlevel" to 1 (instead of default 2, where 1 disables all
rewrites), which worked fine for me. I'll fix this later today. Also
I'll fix the naming from "Choleskey" to "Cholesky". Thanks again.

Regards,
Matthias


On Sat, Apr 21, 2018 at 6:28 PM, Qifan Pu <qifan.pu@gmail.com> wrote:
> Hi Matthias,
>
> Thanks for the fast response and detailed information. This is really
> helpful.
>
> I just tried to run it, and was tracing down a indexing bug that can be
> repeated by simply running the test script of triangle solve[1]
> Caused by: org.apache.sysml.runtime.DMLRuntimeException: Invalid values for
> matrix indexing: [1667:3333,1:1666] must be within matrix dimensions
> [1000,1000]
>
>
> Am I missing some configuration here?
>
>
> [1]
> https://github.com/apache/systemml/blob/master/scripts/staging/scalable_linalg/test/test_triangular_inv.dml
>
>
> Best,
> Qifan
>
>
> On Sat, Apr 21, 2018 at 4:06 PM, Matthias Boehm <mboehm7@gmail.com> wrote:
>>
>> Hi Qifan,
>>
>> thanks for your feedback. You're right, the builtin functions
>> cholesky, inverse, eigen, solve, svd, qr, and lu are currently only
>> supported as single-node operations because they're still implemented
>> via Apache commons.math.
>>
>> However, there is an experimental script for distributed cholesky [1]
>> which uses a recursive approach (with operations that allow for
>> automatic distributed computation) for matrices larger than a
>> user-defined block size. Once blocks become small enough, we use again
>> the builtin cholesky. Graduating this script would require a broader
>> set of experiments (and potential improvements) but it simply did not
>> have the highest priority so far. You might want to give it a try
>> though.
>>
>> Thanks again for your feedback - we'll consider a higher priority for
>> these distributed operations when discussing the roadmap for the next
>> releases.
>>
>> [1]
>> https://github.com/apache/systemml/blob/master/scripts/staging/scalable_linalg/cholesky.dml
>>
>> Regards,
>> Matthias
>>
>> On Sat, Apr 21, 2018 at 2:15 PM, Qifan Pu <qifan.pu@gmail.com> wrote:
>> > Hi,
>> >
>> > I would love to do distributed cholesky on large matrix with SystemML. I
>> > found two related jiras (SYSTEMML-1213, SYSTEMML-1163), but AFAIK, this
>> > is
>> > currently not implemented? I just wanted to check.
>> >
>> > Best,
>> > Qifan
>
>

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