[jira] [Comment Edited] (SYSTEMML-776) Update SystemML to Support Spark 2.0.0
[
https://issues.apache.org/jira/browse/SYSTEMML-776?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15403266#comment-15403266
]
Glenn Weidner edited comment on SYSTEMML-776 at 8/2/16 2:48 AM:
Submitted initial [PR
#202|https://github.com/apache/incubator-systemml/pull/202].
was (Author: gweidner):
Submitted initial [PR|https://github.com/apache/incubator-systemml/pull/202].
> Update SystemML to Support Spark 2.0.0
> --
>
> Key: SYSTEMML-776
> URL: https://issues.apache.org/jira/browse/SYSTEMML-776
> Project: SystemML
> Issue Type: Improvement
>Affects Versions: SystemML 0.9, SystemML 0.10, SystemML 0.11
>Reporter: Mike Dusenberry
>Assignee: Glenn Weidner
>Priority: Critical
>
> In the upcoming Spark 2.0.0 release, the {{DataFrame}} class has been changed
> to a Scala type pointing to {{DataSet[Row]}}, with no {{DataFrame}} available
> from Java. Therefore, our current build is not compatible with this upcoming
> release. This can be tested by updating the pom to using {{2.0.0-preview}}
> as the Spark version.
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[jira] [Commented] (SYSTEMML-776) Update SystemML to Support Spark 2.0.0
[
https://issues.apache.org/jira/browse/SYSTEMML-776?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15403266#comment-15403266
]
Glenn Weidner commented on SYSTEMML-776:
Submitted initial [PR|https://github.com/apache/incubator-systemml/pull/202].
> Update SystemML to Support Spark 2.0.0
> --
>
> Key: SYSTEMML-776
> URL: https://issues.apache.org/jira/browse/SYSTEMML-776
> Project: SystemML
> Issue Type: Improvement
>Affects Versions: SystemML 0.9, SystemML 0.10, SystemML 0.11
>Reporter: Mike Dusenberry
>Assignee: Glenn Weidner
>Priority: Critical
>
> In the upcoming Spark 2.0.0 release, the {{DataFrame}} class has been changed
> to a Scala type pointing to {{DataSet[Row]}}, with no {{DataFrame}} available
> from Java. Therefore, our current build is not compatible with this upcoming
> release. This can be tested by updating the pom to using {{2.0.0-preview}}
> as the Spark version.
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[jira] [Assigned] (SYSTEMML-842) Remove useless javadoc comments and fix javadoc warnings
[ https://issues.apache.org/jira/browse/SYSTEMML-842?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Deron Eriksson reassigned SYSTEMML-842: --- Assignee: Deron Eriksson > Remove useless javadoc comments and fix javadoc warnings > > > Key: SYSTEMML-842 > URL: https://issues.apache.org/jira/browse/SYSTEMML-842 > Project: SystemML > Issue Type: Task > Components: Documentation >Reporter: Deron Eriksson >Assignee: Deron Eriksson > > The project contains an enormous number of useless empty javadoc comments. In > addition, it has many other javadoc warnings. -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[jira] [Updated] (SYSTEMML-843) leftIndex and cache release extremely slow
[
https://issues.apache.org/jira/browse/SYSTEMML-843?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Imran Younus updated SYSTEMML-843:
--
Description:
I'm running the tSNE script in standalone mode with a subset of MNIST data
(2500 points). I ran this with and without `-exec singlenode`. Here are the
stats:
(BTW, the same function implemented in python takes less than 10 sec!)
-> with singlenode flag
{code}
./bin/systemml scripts/staging/tSNE.dml -stats -nvargs
X=/home/iyounus/workspace/tsne_python/mnist2500_X.txt Y=Y_out.txt C=C_out.txt
16/08/01 16:46:54 INFO api.DMLScript: SystemML Statistics:
Total elapsed time: 109.667 sec.
Total compilation time: 0.407 sec.
Total execution time: 109.260 sec.
Number of compiled MR Jobs: 0.
Number of executed MR Jobs: 0.
Cache hits (Mem, WB, FS, HDFS): 223692/0/0/1.
Cache writes (WB, FS, HDFS):80351/0/2.
Cache times (ACQr/m, RLS, EXP): 0.289/0.015/85.192/0.043 sec.
HOP DAGs recompiled (PRED, SB): 0/0.
HOP DAGs recompile time:0.007 sec.
Functions recompiled: 1.
Functions recompile time: 0.039 sec.
Total JIT compile time: 4.924 sec.
Total JVM GC count: 312.
Total JVM GC time: 1.12 sec.
Heavy hitter instructions (name, time, count):
-- 1) tsne109.202 sec 1
-- 2) x2p 109.189 sec 1
-- 3) leftIndex 106.728 sec 32136
-- 4) tsmm0.564 sec 1
-- 5) exp 0.376 sec 8034
-- 6) rangeReIndex0.201 sec 40170
-- 7) / 0.183 sec 24103
-- 8) * 0.161 sec 16069
-- 9) + 0.144 sec 22840
-- 10) uak+0.106 sec 8036
16/08/01 16:46:54 INFO api.DMLScript: END DML run 08/01/2016 16:46:54
{code}
-> without singlenode flag
{code}
> ./bin/systemml scripts/staging/tSNE.dml -stats -nvargs
> X=/home/iyounus/workspace/tsne_python/mnist2500_X.txt Y=Y_out.txt C=C_out.txt
16/08/01 16:52:59 INFO api.DMLScript: SystemML Statistics:
Total elapsed time: 127.290 sec.
Total compilation time: 0.396 sec.
Total execution time: 126.894 sec.
Number of compiled MR Jobs: 1.
Number of executed MR Jobs: 0.
Cache hits (Mem, WB, FS, HDFS): 223693/0/0/1.
Cache writes (WB, FS, HDFS):80352/0/2.
Cache times (ACQr/m, RLS, EXP): 0.421/0.016/100.974/0.041 sec.
HOP DAGs recompiled (PRED, SB): 0/0.
HOP DAGs recompile time:0.009 sec.
Functions recompiled: 1.
Functions recompile time: 0.038 sec.
Total JIT compile time: 4.835 sec.
Total JVM GC count: 312.
Total JVM GC time: 1.226 sec.
Heavy hitter instructions (name, time, count):
-- 1) tsne126.426 sec 1
-- 2) x2p 126.412 sec 1
-- 3) leftIndex 123.982 sec 32136
-- 4) exp 0.427 sec 8034
-- 5) MR-Job_CSV_REBLOCK 0.412 sec 1
-- 6) tsmm0.308 sec 1
-- 7) rangeReIndex0.242 sec 40170
-- 8) / 0.208 sec 24103
-- 9) + 0.172 sec 22840
-- 10) * 0.151 sec 16069
16/08/01 16:52:59 INFO api.DMLScript: END DML run 08/01/2016 16:52:59
{code}
was:
I'm running the tSNE script in standalone mode with a subset of MNIST data
(2500 points). I ran this with and without `-exec singlenode`. Here are the
stats:
-> with singlenode flag
{code}
./bin/systemml scripts/staging/tSNE.dml -stats -nvargs
X=/home/iyounus/workspace/tsne_python/mnist2500_X.txt Y=Y_out.txt C=C_out.txt
16/08/01 16:46:54 INFO api.DMLScript: SystemML Statistics:
Total elapsed time: 109.667 sec.
Total compilation time: 0.407 sec.
Total execution time: 109.260 sec.
Number of compiled MR Jobs: 0.
Number of executed MR Jobs: 0.
Cache hits (Mem, WB, FS, HDFS): 223692/0/0/1.
Cache writes (WB, FS, HDFS):80351/0/2.
Cache times (ACQr/m, RLS, EXP): 0.289/0.015/85.192/0.043 sec.
HOP DAGs recompiled (PRED, SB): 0/0.
HOP DAGs recompile time:0.007 sec.
Functions recompiled: 1.
Functions recompile time: 0.039 sec.
Total JIT compile time: 4.924 sec.
Total JVM GC count: 312.
Total JVM GC time: 1.12 sec.
Heavy hitter instructions (name, time, count):
-- 1) tsne109.202 sec 1
-- 2) x2p 109.189 sec 1
-- 3) leftIndex 106.728 sec 32136
-- 4) tsmm0.564 sec 1
-- 5) exp 0.376 sec 8034
-- 6) rangeReIndex0.201 sec 40170
-- 7) / 0.183 sec 24103
-- 8) * 0.161 sec 16069
-- 9) + 0.144 sec 22840
-- 10) uak+0.106 sec 8036
16/08/01 16:46:54 INFO api.DMLScript: END DML run 08/01/2016 16:46:54
{code}
-> without singlenode flag
{code}
> ./bin/systemml scripts/staging/tSNE.dml -stats -nvargs
> X=/home/iyounus/workspace/tsne_python/mnist2500_X.txt Y=Y_out.txt C=C_out.txt
16/08/01 16:52:59 INFO api.DMLScript: SystemML Statistics:
Total elapsed time:
[jira] [Commented] (SYSTEMML-843) leftIndex and cache release extremely slow
[
https://issues.apache.org/jira/browse/SYSTEMML-843?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15403076#comment-15403076
]
Imran Younus commented on SYSTEMML-843:
---
[~mboehm7] [~niketanpansare]
> leftIndex and cache release extremely slow
> --
>
> Key: SYSTEMML-843
> URL: https://issues.apache.org/jira/browse/SYSTEMML-843
> Project: SystemML
> Issue Type: Bug
>Reporter: Imran Younus
> Attachments: tSNT.tar.gz
>
>
> I'm running the tSNE script in standalone mode with a subset of MNIST data
> (2500 points). I ran this with and without `-exec singlenode`. Here are the
> stats:
> -> with singlenode flag
> {code}
> ./bin/systemml scripts/staging/tSNE.dml -stats -nvargs
> X=/home/iyounus/workspace/tsne_python/mnist2500_X.txt Y=Y_out.txt C=C_out.txt
> 16/08/01 16:46:54 INFO api.DMLScript: SystemML Statistics:
> Total elapsed time: 109.667 sec.
> Total compilation time: 0.407 sec.
> Total execution time: 109.260 sec.
> Number of compiled MR Jobs: 0.
> Number of executed MR Jobs: 0.
> Cache hits (Mem, WB, FS, HDFS): 223692/0/0/1.
> Cache writes (WB, FS, HDFS): 80351/0/2.
> Cache times (ACQr/m, RLS, EXP): 0.289/0.015/85.192/0.043 sec.
> HOP DAGs recompiled (PRED, SB): 0/0.
> HOP DAGs recompile time: 0.007 sec.
> Functions recompiled: 1.
> Functions recompile time: 0.039 sec.
> Total JIT compile time: 4.924 sec.
> Total JVM GC count: 312.
> Total JVM GC time:1.12 sec.
> Heavy hitter instructions (name, time, count):
> -- 1) tsne109.202 sec 1
> -- 2) x2p 109.189 sec 1
> -- 3) leftIndex 106.728 sec 32136
> -- 4) tsmm0.564 sec 1
> -- 5) exp 0.376 sec 8034
> -- 6) rangeReIndex0.201 sec 40170
> -- 7) / 0.183 sec 24103
> -- 8) * 0.161 sec 16069
> -- 9) + 0.144 sec 22840
> -- 10)uak+0.106 sec 8036
> 16/08/01 16:46:54 INFO api.DMLScript: END DML run 08/01/2016 16:46:54
> {code}
> -> without singlenode flag
> {code}
> > ./bin/systemml scripts/staging/tSNE.dml -stats -nvargs
> > X=/home/iyounus/workspace/tsne_python/mnist2500_X.txt Y=Y_out.txt
> > C=C_out.txt
> 16/08/01 16:52:59 INFO api.DMLScript: SystemML Statistics:
> Total elapsed time: 127.290 sec.
> Total compilation time: 0.396 sec.
> Total execution time: 126.894 sec.
> Number of compiled MR Jobs: 1.
> Number of executed MR Jobs: 0.
> Cache hits (Mem, WB, FS, HDFS): 223693/0/0/1.
> Cache writes (WB, FS, HDFS): 80352/0/2.
> Cache times (ACQr/m, RLS, EXP): 0.421/0.016/100.974/0.041 sec.
> HOP DAGs recompiled (PRED, SB): 0/0.
> HOP DAGs recompile time: 0.009 sec.
> Functions recompiled: 1.
> Functions recompile time: 0.038 sec.
> Total JIT compile time: 4.835 sec.
> Total JVM GC count: 312.
> Total JVM GC time:1.226 sec.
> Heavy hitter instructions (name, time, count):
> -- 1) tsne126.426 sec 1
> -- 2) x2p 126.412 sec 1
> -- 3) leftIndex 123.982 sec 32136
> -- 4) exp 0.427 sec 8034
> -- 5) MR-Job_CSV_REBLOCK 0.412 sec 1
> -- 6) tsmm0.308 sec 1
> -- 7) rangeReIndex0.242 sec 40170
> -- 8) / 0.208 sec 24103
> -- 9) + 0.172 sec 22840
> -- 10)* 0.151 sec 16069
> 16/08/01 16:52:59 INFO api.DMLScript: END DML run 08/01/2016 16:52:59
> {code}
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[jira] [Updated] (SYSTEMML-843) leftIndex and cache release extremely slow
[
https://issues.apache.org/jira/browse/SYSTEMML-843?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Imran Younus updated SYSTEMML-843:
--
Attachment: tSNT.tar.gz
data and code for tSNE test
> leftIndex and cache release extremely slow
> --
>
> Key: SYSTEMML-843
> URL: https://issues.apache.org/jira/browse/SYSTEMML-843
> Project: SystemML
> Issue Type: Bug
>Reporter: Imran Younus
> Attachments: tSNT.tar.gz
>
>
> I'm running the tSNE script in standalone mode with a subset of MNIST data
> (2500 points). I ran this with and without `-exec singlenode`. Here are the
> stats:
> -> with singlenode flag
> {code}
> ./bin/systemml scripts/staging/tSNE.dml -stats -nvargs
> X=/home/iyounus/workspace/tsne_python/mnist2500_X.txt Y=Y_out.txt C=C_out.txt
> 16/08/01 16:46:54 INFO api.DMLScript: SystemML Statistics:
> Total elapsed time: 109.667 sec.
> Total compilation time: 0.407 sec.
> Total execution time: 109.260 sec.
> Number of compiled MR Jobs: 0.
> Number of executed MR Jobs: 0.
> Cache hits (Mem, WB, FS, HDFS): 223692/0/0/1.
> Cache writes (WB, FS, HDFS): 80351/0/2.
> Cache times (ACQr/m, RLS, EXP): 0.289/0.015/85.192/0.043 sec.
> HOP DAGs recompiled (PRED, SB): 0/0.
> HOP DAGs recompile time: 0.007 sec.
> Functions recompiled: 1.
> Functions recompile time: 0.039 sec.
> Total JIT compile time: 4.924 sec.
> Total JVM GC count: 312.
> Total JVM GC time:1.12 sec.
> Heavy hitter instructions (name, time, count):
> -- 1) tsne109.202 sec 1
> -- 2) x2p 109.189 sec 1
> -- 3) leftIndex 106.728 sec 32136
> -- 4) tsmm0.564 sec 1
> -- 5) exp 0.376 sec 8034
> -- 6) rangeReIndex0.201 sec 40170
> -- 7) / 0.183 sec 24103
> -- 8) * 0.161 sec 16069
> -- 9) + 0.144 sec 22840
> -- 10)uak+0.106 sec 8036
> 16/08/01 16:46:54 INFO api.DMLScript: END DML run 08/01/2016 16:46:54
> {code}
> -> without singlenode flag
> {code}
> > ./bin/systemml scripts/staging/tSNE.dml -stats -nvargs
> > X=/home/iyounus/workspace/tsne_python/mnist2500_X.txt Y=Y_out.txt
> > C=C_out.txt
> 16/08/01 16:52:59 INFO api.DMLScript: SystemML Statistics:
> Total elapsed time: 127.290 sec.
> Total compilation time: 0.396 sec.
> Total execution time: 126.894 sec.
> Number of compiled MR Jobs: 1.
> Number of executed MR Jobs: 0.
> Cache hits (Mem, WB, FS, HDFS): 223693/0/0/1.
> Cache writes (WB, FS, HDFS): 80352/0/2.
> Cache times (ACQr/m, RLS, EXP): 0.421/0.016/100.974/0.041 sec.
> HOP DAGs recompiled (PRED, SB): 0/0.
> HOP DAGs recompile time: 0.009 sec.
> Functions recompiled: 1.
> Functions recompile time: 0.038 sec.
> Total JIT compile time: 4.835 sec.
> Total JVM GC count: 312.
> Total JVM GC time:1.226 sec.
> Heavy hitter instructions (name, time, count):
> -- 1) tsne126.426 sec 1
> -- 2) x2p 126.412 sec 1
> -- 3) leftIndex 123.982 sec 32136
> -- 4) exp 0.427 sec 8034
> -- 5) MR-Job_CSV_REBLOCK 0.412 sec 1
> -- 6) tsmm0.308 sec 1
> -- 7) rangeReIndex0.242 sec 40170
> -- 8) / 0.208 sec 24103
> -- 9) + 0.172 sec 22840
> -- 10)* 0.151 sec 16069
> 16/08/01 16:52:59 INFO api.DMLScript: END DML run 08/01/2016 16:52:59
> {code}
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[jira] [Created] (SYSTEMML-843) leftIndex and cache release extremely slow
Imran Younus created SYSTEMML-843:
-
Summary: leftIndex and cache release extremely slow
Key: SYSTEMML-843
URL: https://issues.apache.org/jira/browse/SYSTEMML-843
Project: SystemML
Issue Type: Bug
Reporter: Imran Younus
I'm running the tSNE script in standalone mode with a subset of MNIST data
(2500 points). I ran this with and without `-exec singlenode`. Here are the
stats:
-> with singlenode flag
{code}
./bin/systemml scripts/staging/tSNE.dml -stats -nvargs
X=/home/iyounus/workspace/tsne_python/mnist2500_X.txt Y=Y_out.txt C=C_out.txt
16/08/01 16:46:54 INFO api.DMLScript: SystemML Statistics:
Total elapsed time: 109.667 sec.
Total compilation time: 0.407 sec.
Total execution time: 109.260 sec.
Number of compiled MR Jobs: 0.
Number of executed MR Jobs: 0.
Cache hits (Mem, WB, FS, HDFS): 223692/0/0/1.
Cache writes (WB, FS, HDFS):80351/0/2.
Cache times (ACQr/m, RLS, EXP): 0.289/0.015/85.192/0.043 sec.
HOP DAGs recompiled (PRED, SB): 0/0.
HOP DAGs recompile time:0.007 sec.
Functions recompiled: 1.
Functions recompile time: 0.039 sec.
Total JIT compile time: 4.924 sec.
Total JVM GC count: 312.
Total JVM GC time: 1.12 sec.
Heavy hitter instructions (name, time, count):
-- 1) tsne109.202 sec 1
-- 2) x2p 109.189 sec 1
-- 3) leftIndex 106.728 sec 32136
-- 4) tsmm0.564 sec 1
-- 5) exp 0.376 sec 8034
-- 6) rangeReIndex0.201 sec 40170
-- 7) / 0.183 sec 24103
-- 8) * 0.161 sec 16069
-- 9) + 0.144 sec 22840
-- 10) uak+0.106 sec 8036
16/08/01 16:46:54 INFO api.DMLScript: END DML run 08/01/2016 16:46:54
{code}
-> without singlenode flag
{code}
> ./bin/systemml scripts/staging/tSNE.dml -stats -nvargs
> X=/home/iyounus/workspace/tsne_python/mnist2500_X.txt Y=Y_out.txt C=C_out.txt
16/08/01 16:52:59 INFO api.DMLScript: SystemML Statistics:
Total elapsed time: 127.290 sec.
Total compilation time: 0.396 sec.
Total execution time: 126.894 sec.
Number of compiled MR Jobs: 1.
Number of executed MR Jobs: 0.
Cache hits (Mem, WB, FS, HDFS): 223693/0/0/1.
Cache writes (WB, FS, HDFS):80352/0/2.
Cache times (ACQr/m, RLS, EXP): 0.421/0.016/100.974/0.041 sec.
HOP DAGs recompiled (PRED, SB): 0/0.
HOP DAGs recompile time:0.009 sec.
Functions recompiled: 1.
Functions recompile time: 0.038 sec.
Total JIT compile time: 4.835 sec.
Total JVM GC count: 312.
Total JVM GC time: 1.226 sec.
Heavy hitter instructions (name, time, count):
-- 1) tsne126.426 sec 1
-- 2) x2p 126.412 sec 1
-- 3) leftIndex 123.982 sec 32136
-- 4) exp 0.427 sec 8034
-- 5) MR-Job_CSV_REBLOCK 0.412 sec 1
-- 6) tsmm0.308 sec 1
-- 7) rangeReIndex0.242 sec 40170
-- 8) / 0.208 sec 24103
-- 9) + 0.172 sec 22840
-- 10) * 0.151 sec 16069
16/08/01 16:52:59 INFO api.DMLScript: END DML run 08/01/2016 16:52:59
{code}
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[jira] [Created] (SYSTEMML-842) Remove useless javadoc comments and fix javadoc warnings
Deron Eriksson created SYSTEMML-842: --- Summary: Remove useless javadoc comments and fix javadoc warnings Key: SYSTEMML-842 URL: https://issues.apache.org/jira/browse/SYSTEMML-842 Project: SystemML Issue Type: Task Components: Documentation Reporter: Deron Eriksson The project contains an enormous number of useless empty javadoc comments. In addition, it has many other javadoc warnings. -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[jira] [Created] (SYSTEMML-841) Create Java documentation for new MLContext
Deron Eriksson created SYSTEMML-841: --- Summary: Create Java documentation for new MLContext Key: SYSTEMML-841 URL: https://issues.apache.org/jira/browse/SYSTEMML-841 Project: SystemML Issue Type: Task Components: APIs, Documentation Reporter: Deron Eriksson Update MLContext programming guide Java section to use new MLContext -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[jira] [Commented] (SYSTEMML-610) Add Databricks Notebook example to MLContext documentation
[ https://issues.apache.org/jira/browse/SYSTEMML-610?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15402871#comment-15402871 ] Madison J Myers commented on SYSTEMML-610: -- LGTM > Add Databricks Notebook example to MLContext documentation > -- > > Key: SYSTEMML-610 > URL: https://issues.apache.org/jira/browse/SYSTEMML-610 > Project: SystemML > Issue Type: Task >Reporter: Deron Eriksson >Assignee: Deron Eriksson > > Add an example of configuring a Databricks Notebook to use SystemML to the > Spark MLContext Programming Guide. -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[jira] [Commented] (SYSTEMML-824) Improve the performance of binary cell-wise operations
[ https://issues.apache.org/jira/browse/SYSTEMML-824?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15402400#comment-15402400 ] Mike Dusenberry commented on SYSTEMML-824: -- +1 for increased performance > Improve the performance of binary cell-wise operations > -- > > Key: SYSTEMML-824 > URL: https://issues.apache.org/jira/browse/SYSTEMML-824 > Project: SystemML > Issue Type: Task >Reporter: Niketan Pansare > > The cellwise (matrix-matrix as well as matrix-scalar) operations take > significant amount of time while training Lenet. Here are few ways to improve > the performance of cell-wise operations: > 1. Inject in-place updates [1] (saving on zero-ing out the matrix). > 2. Fused cell-wise operations (as an example, recently added axpy operations: > https://github.com/apache/incubator-systemml/commit/b584aecf6b3a1eb96ff83b78cc3ad7c7c6d15baa). > > 3. Parallelize cellwise operations (initial investigation need to be > conducted before proceeding in this direction especially in sparse case: > https://github.com/apache/incubator-systemml/blob/master/src/main/java/org/apache/sysml/runtime/matrix/data/LibMatrixBincell.java#L274). > [~nakul02] [~mwdus...@us.ibm.com] [~prithvi_r_s] [~mboehm7] [~reinwald] > Reference: > [1] http://www.diku.dk/hjemmesider/ansatte/torbenm/ICD/Register.pdf -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[jira] [Created] (SYSTEMML-840) Create Zeppelin docs for new MLContext
Deron Eriksson created SYSTEMML-840: --- Summary: Create Zeppelin docs for new MLContext Key: SYSTEMML-840 URL: https://issues.apache.org/jira/browse/SYSTEMML-840 Project: SystemML Issue Type: Task Components: APIs, Documentation Reporter: Deron Eriksson Update MLContext programming guide Zeppelin section to use new MLContext -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[jira] [Updated] (SYSTEMML-838) Create Spark Shell docs for new MLContext
[ https://issues.apache.org/jira/browse/SYSTEMML-838?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Deron Eriksson updated SYSTEMML-838: Description: Update MLContext programming guide Spark Shell section to use new MLContext > Create Spark Shell docs for new MLContext > - > > Key: SYSTEMML-838 > URL: https://issues.apache.org/jira/browse/SYSTEMML-838 > Project: SystemML > Issue Type: Task > Components: APIs, Documentation >Reporter: Deron Eriksson >Assignee: Deron Eriksson > > Update MLContext programming guide Spark Shell section to use new MLContext -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[jira] [Created] (SYSTEMML-839) Create Jupyter docs for new MLContext
Deron Eriksson created SYSTEMML-839: --- Summary: Create Jupyter docs for new MLContext Key: SYSTEMML-839 URL: https://issues.apache.org/jira/browse/SYSTEMML-839 Project: SystemML Issue Type: Task Components: APIs, Documentation Reporter: Deron Eriksson Update MLContext programming guide Jupyter section to use new MLContext -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[jira] [Created] (SYSTEMML-838) Create Spark Shell docs for new MLContext
Deron Eriksson created SYSTEMML-838: --- Summary: Create Spark Shell docs for new MLContext Key: SYSTEMML-838 URL: https://issues.apache.org/jira/browse/SYSTEMML-838 Project: SystemML Issue Type: Bug Components: APIs, Documentation Reporter: Deron Eriksson Assignee: Deron Eriksson -- This message was sent by Atlassian JIRA (v6.3.4#6332)
[jira] [Updated] (SYSTEMML-838) Create Spark Shell docs for new MLContext
[ https://issues.apache.org/jira/browse/SYSTEMML-838?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Deron Eriksson updated SYSTEMML-838: Issue Type: Task (was: Bug) > Create Spark Shell docs for new MLContext > - > > Key: SYSTEMML-838 > URL: https://issues.apache.org/jira/browse/SYSTEMML-838 > Project: SystemML > Issue Type: Task > Components: APIs, Documentation >Reporter: Deron Eriksson >Assignee: Deron Eriksson > -- This message was sent by Atlassian JIRA (v6.3.4#6332)
