Can a Statistics Services with TERR job run on more than one core?
Article ID: KB0080160
Updated On:
| Products | Versions |
|---|---|
| Spotfire Statistics Services | - |
Description
Customer would like to be able to run multiple TERR jobs on multiple cores on their computer.
Environment
Product: TIBCO Spotfire Statistics Services
Version: All supported versions
OS: All supported Operating Systems
Resolution
Unfortunately this is not available in general in Statistics Services; one job will run on one core.
When you submit a job to Statistics Services with a TERR engine, it will launch a TERR engine through Java. TERR's computation is single-threaded, so it will only use one core. An exception here is that some support functions the BLAS libraries use may be multi-threaded, but this basically only helpful if you are using some specific linear algebra routines.
The other option if you want to use multiple cores is to make use of the parallel package:
parallel
-------------
The parallel package contains a subset of functions to provide
compatibility for open-source R's parallelized computing feature. Using
the TIBCO Enterprise Runtime for R's parallel package, you can:
? Define and create a cluster of TIBCO Enterprise Runtime for R
computation nodes, either locally (multiple cores on a single
machine) or remotely (on multiple machines running TIBCO
Spotfire® Statistics Services).
? Execute a parallelized computation on a cluster using one of a family
of parallelized apply functions.
However, the drawbacks to this are:
1. that you need to re-write your code to make use of these packages
and
2. not all problems are easily parallelized or do not gain much by parallel processing.
When you submit a job to Statistics Services with a TERR engine, it will launch a TERR engine through Java. TERR's computation is single-threaded, so it will only use one core. An exception here is that some support functions the BLAS libraries use may be multi-threaded, but this basically only helpful if you are using some specific linear algebra routines.
The other option if you want to use multiple cores is to make use of the parallel package:
parallel
-------------
The parallel package contains a subset of functions to provide
compatibility for open-source R's parallelized computing feature. Using
the TIBCO Enterprise Runtime for R's parallel package, you can:
? Define and create a cluster of TIBCO Enterprise Runtime for R
computation nodes, either locally (multiple cores on a single
machine) or remotely (on multiple machines running TIBCO
Spotfire® Statistics Services).
? Execute a parallelized computation on a cluster using one of a family
of parallelized apply functions.
However, the drawbacks to this are:
1. that you need to re-write your code to make use of these packages
and
2. not all problems are easily parallelized or do not gain much by parallel processing.
Issue/Introduction
Can a Statistics Services with TERR job run on more than one core?
Feedback
Yes
No
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