Re: Local versions of Linear Algebra Operators in DML
Indeed, some of these operations do allocate additional data structures. Other problems were (1) that our memory estimates do not account for the explicit copy into commons math data structures (e.g., Array2DRowRealMatrix), and (2) unnecessarily raised exceptions due to unknowns. However, both issues can be addressed and since we're talking about warnings, false positives/negatives are probably ok. Regards, Matthias On 10/24/2016 9:35 PM, Berthold Reinwald wrote: if I remember correctly then it is not trivial to accurately estimate the memory foot print for these commons math functions at compile time depending on what intermediates they produce ... Meaning you may still end up with java heap space OOM at runtime. Regards, Berthold Reinwald IBM Almaden Research Center office: (408) 927 2208; T/L: 457 2208 e-mail: reinw...@us.ibm.com From: Matthias Boehm <mboe...@googlemail.com> To: dev@systemml.incubator.apache.org Date: 10/24/2016 11:54 AM Subject: Re: Local versions of Linear Algebra Operators in DML well, we still compute memory estimates for these operations. So I guess, a good compromise would be to raise a warning whenever the memory estimate is known to exceed the local memory budget. Regards, Matthias On 10/24/2016 8:29 PM, Deron Eriksson wrote: Would it be acceptable for a user to receive a log warning if the user uses an operation that is currently only implemented for single node? My concern is that there is an expectation for operations to be distributed with SystemML, and if an operation is not currently distributed, the user needs to made aware of this. Thoughts? Deron On Mon, Oct 24, 2016 at 10:38 AM, Nakul Jindal <naku...@gmail.com> wrote: Hi, There is an initial implementation and PR. https://github.com/apache/incubator-systemml/pull/273 -Nakul On Oct 24, 2016, at 12:59 AM, Berthold Reinwald <reinw...@us.ibm.com> wrote: Thanks, Imran. I think it is a good idea to start off with the DML-bodied function implementation. This will hold until we can have a built in implementation. We prototyped an implementation of distributed Cholesky as a DML bodied function as well. For performance optimization, as the matrix becomes "small" enough, we switched over and exploit a single node implementation. Adding a new svd() built in function that initially routes to a local library is fine. I don't know whether Apache commons math has an implementation that can be re-used. I object renaming the functions or changing the externals. Eventually distributed instructions need to be added to these implementations, and there are open jiras for it. Regards, Berthold Reinwald IBM Almaden Research Center office: (408) 927 2208; T/L: 457 2208 e-mail: reinw...@us.ibm.com From: Niketan Pansare/Almaden/IBM@IBMUS To: dev@systemml.incubator.apache.org Date: 10/21/2016 01:14 PM Subject: Re: Local versions of Linear Algebra Operators in DML I am also comfortable with option (2) ... "with a plan to implement its distributed version" Thanks, Niketan Pansare IBM Almaden Research Center E-mail: npansar At us.ibm.com http://researcher.watson.ibm.com/researcher/view.php?person=us-npansar Matthias Boehm ---10/21/2016 01:00:51 PM---thanks Nakul for reaching out before starting work on this. Actually, the introduction of these CP- From: Matthias Boehm <mboe...@googlemail.com> To: dev@systemml.incubator.apache.org Date: 10/21/2016 01:00 PM Subject: Re: Local versions of Linear Algebra Operators in DML thanks Nakul for reaching out before starting work on this. Actually, the introduction of these CP-only builtin functions was a big mistake because (as you already mentioned) they mistakenly suggest that we provide distributed operations for them too. The intend was to support them in later versions with our own local and distributed implementations. So far, this had low priority though because these O(n^3) operations are seldom used over large data. However, a while back, we lost potential users who were specifically interested in distributed eigen - so there are still use cases. Despite the good intentions behind the renaming, I would strongly argue against it. First, it would unnecessarily lose compatibility with R syntax. Second, it would defeat our clean abstraction by exposing explicit local operations. This leaves us with two options here: (1) you could use an external (java-implemented) function, which gives you virtually the same runtime behavior but a clear separation via an explicit registration, or (2) add it to the list of CP-only operations (with a plan to implement its distributed version) but name it 'svd' as in R. Regards, Matthias On 10/21/2016 9:34 PM, Nakul Jindal wrote: Hi, Imran was planning on implementing a distributed SVD as a DML bodied function. The algorithm is described in the paper titled "A Distributed and Incremental SVD Algorithm for Agglome
Re: Local versions of Linear Algebra Operators in DML
if I remember correctly then it is not trivial to accurately estimate the memory foot print for these commons math functions at compile time depending on what intermediates they produce ... Meaning you may still end up with java heap space OOM at runtime. Regards, Berthold Reinwald IBM Almaden Research Center office: (408) 927 2208; T/L: 457 2208 e-mail: reinw...@us.ibm.com From: Matthias Boehm <mboe...@googlemail.com> To: dev@systemml.incubator.apache.org Date: 10/24/2016 11:54 AM Subject: Re: Local versions of Linear Algebra Operators in DML well, we still compute memory estimates for these operations. So I guess, a good compromise would be to raise a warning whenever the memory estimate is known to exceed the local memory budget. Regards, Matthias On 10/24/2016 8:29 PM, Deron Eriksson wrote: > Would it be acceptable for a user to receive a log warning if the user uses > an operation that is currently only implemented for single node? My concern > is that there is an expectation for operations to be distributed with > SystemML, and if an operation is not currently distributed, the user needs > to made aware of this. > > Thoughts? > > Deron > > > On Mon, Oct 24, 2016 at 10:38 AM, Nakul Jindal <naku...@gmail.com> wrote: > >> Hi, >> >> There is an initial implementation and PR. >> https://github.com/apache/incubator-systemml/pull/273 >> >> -Nakul >> >> >>> On Oct 24, 2016, at 12:59 AM, Berthold Reinwald <reinw...@us.ibm.com> >> wrote: >>> >>> Thanks, Imran. I think it is a good idea to start off with the DML-bodied >>> function implementation. This will hold until we can have a built in >>> implementation. >>> >>> We prototyped an implementation of distributed Cholesky as a DML bodied >>> function as well. For performance optimization, as the matrix becomes >>> "small" enough, we switched over and exploit a single node >> implementation. >>> >>> Adding a new svd() built in function that initially routes to a local >>> library is fine. I don't know whether Apache commons math has an >>> implementation that can be re-used. >>> >>> I object renaming the functions or changing the externals. Eventually >>> distributed instructions need to be added to these implementations, and >>> there are open jiras for it. >>> >>> Regards, >>> Berthold Reinwald >>> IBM Almaden Research Center >>> office: (408) 927 2208; T/L: 457 2208 >>> e-mail: reinw...@us.ibm.com >>> >>> >>> >>> From: Niketan Pansare/Almaden/IBM@IBMUS >>> To: dev@systemml.incubator.apache.org >>> Date: 10/21/2016 01:14 PM >>> Subject:Re: Local versions of Linear Algebra Operators in DML >>> >>> >>> >>> I am also comfortable with option (2) ... "with a plan to implement its >>> distributed version" >>> >>> Thanks, >>> >>> Niketan Pansare >>> IBM Almaden Research Center >>> E-mail: npansar At us.ibm.com >>> http://researcher.watson.ibm.com/researcher/view.php?person=us-npansar >>> >>> Matthias Boehm ---10/21/2016 01:00:51 PM---thanks Nakul for reaching out >>> before starting work on this. Actually, the introduction of these CP- >>> >>> From: Matthias Boehm <mboe...@googlemail.com> >>> To: dev@systemml.incubator.apache.org >>> Date: 10/21/2016 01:00 PM >>> Subject: Re: Local versions of Linear Algebra Operators in DML >>> >>> >>> >>> thanks Nakul for reaching out before starting work on this. Actually, >>> the introduction of these CP-only builtin functions was a big mistake >>> because (as you already mentioned) they mistakenly suggest that we >>> provide distributed operations for them too. The intend was to support >>> them in later versions with our own local and distributed >>> implementations. So far, this had low priority though because these >>> O(n^3) operations are seldom used over large data. However, a while >>> back, we lost potential users who were specifically interested in >>> distributed eigen - so there are still use cases. >>> >>> Despite the good intentions behind the renaming, I would strongly argue >>> against it. First, it would unnecessarily lose compatibility with R >>> syntax. Second, it would defeat our clean abstraction by exposing >>> explicit local operations. >>> >>> This leaves us with two options here: (1) you could us
Re: Local versions of Linear Algebra Operators in DML
well, we still compute memory estimates for these operations. So I guess, a good compromise would be to raise a warning whenever the memory estimate is known to exceed the local memory budget. Regards, Matthias On 10/24/2016 8:29 PM, Deron Eriksson wrote: Would it be acceptable for a user to receive a log warning if the user uses an operation that is currently only implemented for single node? My concern is that there is an expectation for operations to be distributed with SystemML, and if an operation is not currently distributed, the user needs to made aware of this. Thoughts? Deron On Mon, Oct 24, 2016 at 10:38 AM, Nakul Jindal <naku...@gmail.com> wrote: Hi, There is an initial implementation and PR. https://github.com/apache/incubator-systemml/pull/273 -Nakul On Oct 24, 2016, at 12:59 AM, Berthold Reinwald <reinw...@us.ibm.com> wrote: Thanks, Imran. I think it is a good idea to start off with the DML-bodied function implementation. This will hold until we can have a built in implementation. We prototyped an implementation of distributed Cholesky as a DML bodied function as well. For performance optimization, as the matrix becomes "small" enough, we switched over and exploit a single node implementation. Adding a new svd() built in function that initially routes to a local library is fine. I don't know whether Apache commons math has an implementation that can be re-used. I object renaming the functions or changing the externals. Eventually distributed instructions need to be added to these implementations, and there are open jiras for it. Regards, Berthold Reinwald IBM Almaden Research Center office: (408) 927 2208; T/L: 457 2208 e-mail: reinw...@us.ibm.com From: Niketan Pansare/Almaden/IBM@IBMUS To: dev@systemml.incubator.apache.org Date: 10/21/2016 01:14 PM Subject:Re: Local versions of Linear Algebra Operators in DML I am also comfortable with option (2) ... "with a plan to implement its distributed version" Thanks, Niketan Pansare IBM Almaden Research Center E-mail: npansar At us.ibm.com http://researcher.watson.ibm.com/researcher/view.php?person=us-npansar Matthias Boehm ---10/21/2016 01:00:51 PM---thanks Nakul for reaching out before starting work on this. Actually, the introduction of these CP- From: Matthias Boehm <mboe...@googlemail.com> To: dev@systemml.incubator.apache.org Date: 10/21/2016 01:00 PM Subject: Re: Local versions of Linear Algebra Operators in DML thanks Nakul for reaching out before starting work on this. Actually, the introduction of these CP-only builtin functions was a big mistake because (as you already mentioned) they mistakenly suggest that we provide distributed operations for them too. The intend was to support them in later versions with our own local and distributed implementations. So far, this had low priority though because these O(n^3) operations are seldom used over large data. However, a while back, we lost potential users who were specifically interested in distributed eigen - so there are still use cases. Despite the good intentions behind the renaming, I would strongly argue against it. First, it would unnecessarily lose compatibility with R syntax. Second, it would defeat our clean abstraction by exposing explicit local operations. This leaves us with two options here: (1) you could use an external (java-implemented) function, which gives you virtually the same runtime behavior but a clear separation via an explicit registration, or (2) add it to the list of CP-only operations (with a plan to implement its distributed version) but name it 'svd' as in R. Regards, Matthias On 10/21/2016 9:34 PM, Nakul Jindal wrote: Hi, Imran was planning on implementing a distributed SVD as a DML bodied function. The algorithm is described in the paper titled "A Distributed and Incremental SVD Algorithm for Agglomerative Data Analysis on Large Networks" available at https://arxiv.org/abs/1601.07010. This algorithm requires the availability of a local SVD function, which we currently do not have in SystemML. Seeing as how there are other linear algebra functions (eigen, lu, qr, cholesky) in DML that reroute to Apache Common Math and only operate in standalone/CP mode, would it be ok to add "svd" to this set? Also, since these operations are local and not distributed and the documentation doesn't make it clear that these operations wont operate in distributed mode, would it make sense to rename them to "local_eigen", "local_qr", "local_cholesky", etc? Obviously, this change would go into the version after 0.11. I understand that the ideal solution to this problem is to have a distributed version of the aforementioned linear algebra routines, but for the time being, would it be ok to go ahead do the rename, while also introducing a "local_svd" ? Niketan, Berthold, Matthias, Sasha - Any thoughts? Thanks, Nakul Jindal
Re: Local versions of Linear Algebra Operators in DML
Would it be acceptable for a user to receive a log warning if the user uses an operation that is currently only implemented for single node? My concern is that there is an expectation for operations to be distributed with SystemML, and if an operation is not currently distributed, the user needs to made aware of this. Thoughts? Deron On Mon, Oct 24, 2016 at 10:38 AM, Nakul Jindal <naku...@gmail.com> wrote: > Hi, > > There is an initial implementation and PR. > https://github.com/apache/incubator-systemml/pull/273 > > -Nakul > > > > On Oct 24, 2016, at 12:59 AM, Berthold Reinwald <reinw...@us.ibm.com> > wrote: > > > > Thanks, Imran. I think it is a good idea to start off with the DML-bodied > > function implementation. This will hold until we can have a built in > > implementation. > > > > We prototyped an implementation of distributed Cholesky as a DML bodied > > function as well. For performance optimization, as the matrix becomes > > "small" enough, we switched over and exploit a single node > implementation. > > > > Adding a new svd() built in function that initially routes to a local > > library is fine. I don't know whether Apache commons math has an > > implementation that can be re-used. > > > > I object renaming the functions or changing the externals. Eventually > > distributed instructions need to be added to these implementations, and > > there are open jiras for it. > > > > Regards, > > Berthold Reinwald > > IBM Almaden Research Center > > office: (408) 927 2208; T/L: 457 2208 > > e-mail: reinw...@us.ibm.com > > > > > > > > From: Niketan Pansare/Almaden/IBM@IBMUS > > To: dev@systemml.incubator.apache.org > > Date: 10/21/2016 01:14 PM > > Subject:Re: Local versions of Linear Algebra Operators in DML > > > > > > > > I am also comfortable with option (2) ... "with a plan to implement its > > distributed version" > > > > Thanks, > > > > Niketan Pansare > > IBM Almaden Research Center > > E-mail: npansar At us.ibm.com > > http://researcher.watson.ibm.com/researcher/view.php?person=us-npansar > > > > Matthias Boehm ---10/21/2016 01:00:51 PM---thanks Nakul for reaching out > > before starting work on this. Actually, the introduction of these CP- > > > > From: Matthias Boehm <mboe...@googlemail.com> > > To: dev@systemml.incubator.apache.org > > Date: 10/21/2016 01:00 PM > > Subject: Re: Local versions of Linear Algebra Operators in DML > > > > > > > > thanks Nakul for reaching out before starting work on this. Actually, > > the introduction of these CP-only builtin functions was a big mistake > > because (as you already mentioned) they mistakenly suggest that we > > provide distributed operations for them too. The intend was to support > > them in later versions with our own local and distributed > > implementations. So far, this had low priority though because these > > O(n^3) operations are seldom used over large data. However, a while > > back, we lost potential users who were specifically interested in > > distributed eigen - so there are still use cases. > > > > Despite the good intentions behind the renaming, I would strongly argue > > against it. First, it would unnecessarily lose compatibility with R > > syntax. Second, it would defeat our clean abstraction by exposing > > explicit local operations. > > > > This leaves us with two options here: (1) you could use an external > > (java-implemented) function, which gives you virtually the same runtime > > behavior but a clear separation via an explicit registration, or (2) add > > it to the list of CP-only operations (with a plan to implement its > > distributed version) but name it 'svd' as in R. > > > > > > Regards, > > Matthias > > > > > >> On 10/21/2016 9:34 PM, Nakul Jindal wrote: > >> Hi, > >> > >> Imran was planning on implementing a distributed SVD as a DML bodied > >> function. > >> The algorithm is described in the paper titled "A Distributed and > >> Incremental SVD Algorithm for Agglomerative Data Analysis on Large > >> Networks" available at https://arxiv.org/abs/1601.07010. > >> > >> This algorithm requires the availability of a local SVD function, which > > we > >> currently do not have in SystemML. > >> Seeing as how there are other linear algebra functions (eigen, lu, qr, > >> cholesky) in DML that reroute to Apache Common Math and only operate
Re: Local versions of Linear Algebra Operators in DML
Hi, There is an initial implementation and PR. https://github.com/apache/incubator-systemml/pull/273 -Nakul > On Oct 24, 2016, at 12:59 AM, Berthold Reinwald <reinw...@us.ibm.com> wrote: > > Thanks, Imran. I think it is a good idea to start off with the DML-bodied > function implementation. This will hold until we can have a built in > implementation. > > We prototyped an implementation of distributed Cholesky as a DML bodied > function as well. For performance optimization, as the matrix becomes > "small" enough, we switched over and exploit a single node implementation. > > Adding a new svd() built in function that initially routes to a local > library is fine. I don't know whether Apache commons math has an > implementation that can be re-used. > > I object renaming the functions or changing the externals. Eventually > distributed instructions need to be added to these implementations, and > there are open jiras for it. > > Regards, > Berthold Reinwald > IBM Almaden Research Center > office: (408) 927 2208; T/L: 457 2208 > e-mail: reinw...@us.ibm.com > > > > From: Niketan Pansare/Almaden/IBM@IBMUS > To: dev@systemml.incubator.apache.org > Date: 10/21/2016 01:14 PM > Subject:Re: Local versions of Linear Algebra Operators in DML > > > > I am also comfortable with option (2) ... "with a plan to implement its > distributed version" > > Thanks, > > Niketan Pansare > IBM Almaden Research Center > E-mail: npansar At us.ibm.com > http://researcher.watson.ibm.com/researcher/view.php?person=us-npansar > > Matthias Boehm ---10/21/2016 01:00:51 PM---thanks Nakul for reaching out > before starting work on this. Actually, the introduction of these CP- > > From: Matthias Boehm <mboe...@googlemail.com> > To: dev@systemml.incubator.apache.org > Date: 10/21/2016 01:00 PM > Subject: Re: Local versions of Linear Algebra Operators in DML > > > > thanks Nakul for reaching out before starting work on this. Actually, > the introduction of these CP-only builtin functions was a big mistake > because (as you already mentioned) they mistakenly suggest that we > provide distributed operations for them too. The intend was to support > them in later versions with our own local and distributed > implementations. So far, this had low priority though because these > O(n^3) operations are seldom used over large data. However, a while > back, we lost potential users who were specifically interested in > distributed eigen - so there are still use cases. > > Despite the good intentions behind the renaming, I would strongly argue > against it. First, it would unnecessarily lose compatibility with R > syntax. Second, it would defeat our clean abstraction by exposing > explicit local operations. > > This leaves us with two options here: (1) you could use an external > (java-implemented) function, which gives you virtually the same runtime > behavior but a clear separation via an explicit registration, or (2) add > it to the list of CP-only operations (with a plan to implement its > distributed version) but name it 'svd' as in R. > > > Regards, > Matthias > > >> On 10/21/2016 9:34 PM, Nakul Jindal wrote: >> Hi, >> >> Imran was planning on implementing a distributed SVD as a DML bodied >> function. >> The algorithm is described in the paper titled "A Distributed and >> Incremental SVD Algorithm for Agglomerative Data Analysis on Large >> Networks" available at https://arxiv.org/abs/1601.07010. >> >> This algorithm requires the availability of a local SVD function, which > we >> currently do not have in SystemML. >> Seeing as how there are other linear algebra functions (eigen, lu, qr, >> cholesky) in DML that reroute to Apache Common Math and only operate in >> standalone/CP mode, would it be ok to add "svd" to this set? >> >> Also, since these operations are local and not distributed and the >> documentation doesn't make it clear that these operations wont operate > in >> distributed mode, would it make sense to rename them to "local_eigen", >> "local_qr", "local_cholesky", etc? >> Obviously, this change would go into the version after 0.11. >> >> I understand that the ideal solution to this problem is to have a >> distributed version of the aforementioned linear algebra routines, but > for >> the time being, would it be ok to go ahead do the rename, while also >> introducing a "local_svd" ? >> >> >> Niketan, Berthold, Matthias, Sasha - Any thoughts? >> >> Thanks, >> Nakul Jindal >> > > > > > > >
Re: Local versions of Linear Algebra Operators in DML
Thanks, Imran. I think it is a good idea to start off with the DML-bodied function implementation. This will hold until we can have a built in implementation. We prototyped an implementation of distributed Cholesky as a DML bodied function as well. For performance optimization, as the matrix becomes "small" enough, we switched over and exploit a single node implementation. Adding a new svd() built in function that initially routes to a local library is fine. I don't know whether Apache commons math has an implementation that can be re-used. I object renaming the functions or changing the externals. Eventually distributed instructions need to be added to these implementations, and there are open jiras for it. Regards, Berthold Reinwald IBM Almaden Research Center office: (408) 927 2208; T/L: 457 2208 e-mail: reinw...@us.ibm.com From: Niketan Pansare/Almaden/IBM@IBMUS To: dev@systemml.incubator.apache.org Date: 10/21/2016 01:14 PM Subject: Re: Local versions of Linear Algebra Operators in DML I am also comfortable with option (2) ... "with a plan to implement its distributed version" Thanks, Niketan Pansare IBM Almaden Research Center E-mail: npansar At us.ibm.com http://researcher.watson.ibm.com/researcher/view.php?person=us-npansar Matthias Boehm ---10/21/2016 01:00:51 PM---thanks Nakul for reaching out before starting work on this. Actually, the introduction of these CP- From: Matthias Boehm <mboe...@googlemail.com> To: dev@systemml.incubator.apache.org Date: 10/21/2016 01:00 PM Subject: Re: Local versions of Linear Algebra Operators in DML thanks Nakul for reaching out before starting work on this. Actually, the introduction of these CP-only builtin functions was a big mistake because (as you already mentioned) they mistakenly suggest that we provide distributed operations for them too. The intend was to support them in later versions with our own local and distributed implementations. So far, this had low priority though because these O(n^3) operations are seldom used over large data. However, a while back, we lost potential users who were specifically interested in distributed eigen - so there are still use cases. Despite the good intentions behind the renaming, I would strongly argue against it. First, it would unnecessarily lose compatibility with R syntax. Second, it would defeat our clean abstraction by exposing explicit local operations. This leaves us with two options here: (1) you could use an external (java-implemented) function, which gives you virtually the same runtime behavior but a clear separation via an explicit registration, or (2) add it to the list of CP-only operations (with a plan to implement its distributed version) but name it 'svd' as in R. Regards, Matthias On 10/21/2016 9:34 PM, Nakul Jindal wrote: > Hi, > > Imran was planning on implementing a distributed SVD as a DML bodied > function. > The algorithm is described in the paper titled "A Distributed and > Incremental SVD Algorithm for Agglomerative Data Analysis on Large > Networks" available at https://arxiv.org/abs/1601.07010. > > This algorithm requires the availability of a local SVD function, which we > currently do not have in SystemML. > Seeing as how there are other linear algebra functions (eigen, lu, qr, > cholesky) in DML that reroute to Apache Common Math and only operate in > standalone/CP mode, would it be ok to add "svd" to this set? > > Also, since these operations are local and not distributed and the > documentation doesn't make it clear that these operations wont operate in > distributed mode, would it make sense to rename them to "local_eigen", > "local_qr", "local_cholesky", etc? > Obviously, this change would go into the version after 0.11. > > I understand that the ideal solution to this problem is to have a > distributed version of the aforementioned linear algebra routines, but for > the time being, would it be ok to go ahead do the rename, while also > introducing a "local_svd" ? > > > Niketan, Berthold, Matthias, Sasha - Any thoughts? > > Thanks, > Nakul Jindal >
Re: Local versions of Linear Algebra Operators in DML
I am also comfortable with option (2) ... "with a plan to implement its distributed version" Thanks, Niketan Pansare IBM Almaden Research Center E-mail: npansar At us.ibm.com http://researcher.watson.ibm.com/researcher/view.php?person=us-npansar From: Matthias Boehm <mboe...@googlemail.com> To: dev@systemml.incubator.apache.org Date: 10/21/2016 01:00 PM Subject: Re: Local versions of Linear Algebra Operators in DML thanks Nakul for reaching out before starting work on this. Actually, the introduction of these CP-only builtin functions was a big mistake because (as you already mentioned) they mistakenly suggest that we provide distributed operations for them too. The intend was to support them in later versions with our own local and distributed implementations. So far, this had low priority though because these O(n^3) operations are seldom used over large data. However, a while back, we lost potential users who were specifically interested in distributed eigen - so there are still use cases. Despite the good intentions behind the renaming, I would strongly argue against it. First, it would unnecessarily lose compatibility with R syntax. Second, it would defeat our clean abstraction by exposing explicit local operations. This leaves us with two options here: (1) you could use an external (java-implemented) function, which gives you virtually the same runtime behavior but a clear separation via an explicit registration, or (2) add it to the list of CP-only operations (with a plan to implement its distributed version) but name it 'svd' as in R. Regards, Matthias On 10/21/2016 9:34 PM, Nakul Jindal wrote: > Hi, > > Imran was planning on implementing a distributed SVD as a DML bodied > function. > The algorithm is described in the paper titled "A Distributed and > Incremental SVD Algorithm for Agglomerative Data Analysis on Large > Networks" available at https://arxiv.org/abs/1601.07010. > > This algorithm requires the availability of a local SVD function, which we > currently do not have in SystemML. > Seeing as how there are other linear algebra functions (eigen, lu, qr, > cholesky) in DML that reroute to Apache Common Math and only operate in > standalone/CP mode, would it be ok to add "svd" to this set? > > Also, since these operations are local and not distributed and the > documentation doesn't make it clear that these operations wont operate in > distributed mode, would it make sense to rename them to "local_eigen", > "local_qr", "local_cholesky", etc? > Obviously, this change would go into the version after 0.11. > > I understand that the ideal solution to this problem is to have a > distributed version of the aforementioned linear algebra routines, but for > the time being, would it be ok to go ahead do the rename, while also > introducing a "local_svd" ? > > > Niketan, Berthold, Matthias, Sasha - Any thoughts? > > Thanks, > Nakul Jindal >
Re: Local versions of Linear Algebra Operators in DML
Hi Nakul, I really don't like the fact that eigen, lu, qr, cholesky only have local implementation and we have qualified them to the status of builtin functions. We should definitely consider the option of implementing a SPARK instructions for them (as you mentioned in the email) before we officially mark them to "local_only". In fact, instead of marking them as "local_only", I would much rather prefer to support them as external builtin functions. Thanks, Niketan Pansare IBM Almaden Research Center E-mail: npansar At us.ibm.com http://researcher.watson.ibm.com/researcher/view.php?person=us-npansar From: Deron Eriksson <deroneriks...@gmail.com> To: dev@systemml.incubator.apache.org Date: 10/21/2016 12:52 PM Subject:Re: Local versions of Linear Algebra Operators in DML Hi Nakul, +1 I think having some clear characteristic to distinguish operations that only operate locally is a great idea. Otherwise, how would a user know that these operations are only local and not distributed? Adding this naming convention for local operations sounds reasonable to me so that we don't anger users who expect an operation to be distributed when in actuality it only currently runs locally. Deron On Fri, Oct 21, 2016 at 12:34 PM, Nakul Jindal <naku...@gmail.com> wrote: > Hi, > > Imran was planning on implementing a distributed SVD as a DML bodied > function. > The algorithm is described in the paper titled "A Distributed and > Incremental SVD Algorithm for Agglomerative Data Analysis on Large > Networks" available at https://arxiv.org/abs/1601.07010. > > This algorithm requires the availability of a local SVD function, which we > currently do not have in SystemML. > Seeing as how there are other linear algebra functions (eigen, lu, qr, > cholesky) in DML that reroute to Apache Common Math and only operate in > standalone/CP mode, would it be ok to add "svd" to this set? > > Also, since these operations are local and not distributed and the > documentation doesn't make it clear that these operations wont operate in > distributed mode, would it make sense to rename them to "local_eigen", > "local_qr", "local_cholesky", etc? > Obviously, this change would go into the version after 0.11. > > I understand that the ideal solution to this problem is to have a > distributed version of the aforementioned linear algebra routines, but for > the time being, would it be ok to go ahead do the rename, while also > introducing a "local_svd" ? > > > Niketan, Berthold, Matthias, Sasha - Any thoughts? > > Thanks, > Nakul Jindal >
Re: Local versions of Linear Algebra Operators in DML
thanks Nakul for reaching out before starting work on this. Actually, the introduction of these CP-only builtin functions was a big mistake because (as you already mentioned) they mistakenly suggest that we provide distributed operations for them too. The intend was to support them in later versions with our own local and distributed implementations. So far, this had low priority though because these O(n^3) operations are seldom used over large data. However, a while back, we lost potential users who were specifically interested in distributed eigen - so there are still use cases. Despite the good intentions behind the renaming, I would strongly argue against it. First, it would unnecessarily lose compatibility with R syntax. Second, it would defeat our clean abstraction by exposing explicit local operations. This leaves us with two options here: (1) you could use an external (java-implemented) function, which gives you virtually the same runtime behavior but a clear separation via an explicit registration, or (2) add it to the list of CP-only operations (with a plan to implement its distributed version) but name it 'svd' as in R. Regards, Matthias On 10/21/2016 9:34 PM, Nakul Jindal wrote: Hi, Imran was planning on implementing a distributed SVD as a DML bodied function. The algorithm is described in the paper titled "A Distributed and Incremental SVD Algorithm for Agglomerative Data Analysis on Large Networks" available at https://arxiv.org/abs/1601.07010. This algorithm requires the availability of a local SVD function, which we currently do not have in SystemML. Seeing as how there are other linear algebra functions (eigen, lu, qr, cholesky) in DML that reroute to Apache Common Math and only operate in standalone/CP mode, would it be ok to add "svd" to this set? Also, since these operations are local and not distributed and the documentation doesn't make it clear that these operations wont operate in distributed mode, would it make sense to rename them to "local_eigen", "local_qr", "local_cholesky", etc? Obviously, this change would go into the version after 0.11. I understand that the ideal solution to this problem is to have a distributed version of the aforementioned linear algebra routines, but for the time being, would it be ok to go ahead do the rename, while also introducing a "local_svd" ? Niketan, Berthold, Matthias, Sasha - Any thoughts? Thanks, Nakul Jindal
Re: Local versions of Linear Algebra Operators in DML
Hi Nakul, +1 I think having some clear characteristic to distinguish operations that only operate locally is a great idea. Otherwise, how would a user know that these operations are only local and not distributed? Adding this naming convention for local operations sounds reasonable to me so that we don't anger users who expect an operation to be distributed when in actuality it only currently runs locally. Deron On Fri, Oct 21, 2016 at 12:34 PM, Nakul Jindalwrote: > Hi, > > Imran was planning on implementing a distributed SVD as a DML bodied > function. > The algorithm is described in the paper titled "A Distributed and > Incremental SVD Algorithm for Agglomerative Data Analysis on Large > Networks" available at https://arxiv.org/abs/1601.07010. > > This algorithm requires the availability of a local SVD function, which we > currently do not have in SystemML. > Seeing as how there are other linear algebra functions (eigen, lu, qr, > cholesky) in DML that reroute to Apache Common Math and only operate in > standalone/CP mode, would it be ok to add "svd" to this set? > > Also, since these operations are local and not distributed and the > documentation doesn't make it clear that these operations wont operate in > distributed mode, would it make sense to rename them to "local_eigen", > "local_qr", "local_cholesky", etc? > Obviously, this change would go into the version after 0.11. > > I understand that the ideal solution to this problem is to have a > distributed version of the aforementioned linear algebra routines, but for > the time being, would it be ok to go ahead do the rename, while also > introducing a "local_svd" ? > > > Niketan, Berthold, Matthias, Sasha - Any thoughts? > > Thanks, > Nakul Jindal >
Local versions of Linear Algebra Operators in DML
Hi, Imran was planning on implementing a distributed SVD as a DML bodied function. The algorithm is described in the paper titled "A Distributed and Incremental SVD Algorithm for Agglomerative Data Analysis on Large Networks" available at https://arxiv.org/abs/1601.07010. This algorithm requires the availability of a local SVD function, which we currently do not have in SystemML. Seeing as how there are other linear algebra functions (eigen, lu, qr, cholesky) in DML that reroute to Apache Common Math and only operate in standalone/CP mode, would it be ok to add "svd" to this set? Also, since these operations are local and not distributed and the documentation doesn't make it clear that these operations wont operate in distributed mode, would it make sense to rename them to "local_eigen", "local_qr", "local_cholesky", etc? Obviously, this change would go into the version after 0.11. I understand that the ideal solution to this problem is to have a distributed version of the aforementioned linear algebra routines, but for the time being, would it be ok to go ahead do the rename, while also introducing a "local_svd" ? Niketan, Berthold, Matthias, Sasha - Any thoughts? Thanks, Nakul Jindal