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Dual core processor
- Dieses Thema hat 4 Antworten sowie 3 Teilnehmer und wurde zuletzt vor vor 17 Jahren, 8 Monaten von norbert.bakkers@lr.org aktualisiert.
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AutorBeiträge
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März 26, 2007 um 4:05 am Uhr #12641norbert.bakkers@lr.orgTeilnehmer
The computer that runs Flexpro applications has a dual core processor (Intel T2600 @ 2.16 GHz). The processor usage never exceeds 50% (100% of 1 processor) even when using very processor intense Flexpro applications when the HDD is not very active.
Is this a known problem, or is this something that can easily be rectified?
Computer is HP laptop nw8440 running XP professional SP2 and Flexpro 7.März 26, 2007 um 4:05 am Uhr #8304norbert.bakkers@lr.orgTeilnehmerThe computer that runs Flexpro applications has a dual core processor (Intel T2600 @ 2.16 GHz). The processor usage never exceeds 50% (100% of 1 processor) even when using very processor intense Flexpro applications when the HDD is not very active.
Is this a known problem, or is this something that can easily be rectified?
Computer is HP laptop nw8440 running XP professional SP2 and Flexpro 7.März 26, 2007 um 6:23 pm Uhr #9038Bernhard KantzTeilnehmerFlexPro7 is mainly single-threaded.
But this will change in FlexPro8. Then FlexPro will use multiple parallel processes for the mathematical calculations. That means all existing processors in a multi core system will be used.April 9, 2010 um 10:24 pm Uhr #9039John HuxtableMitgliedWe are running 8.0.24 on a Xeon, quad core, processor but do not seem to benefit from multiple cores. Is there a setting somewhere in Windows or Flexpro to make use of the processing power?
April 10, 2010 um 1:08 am Uhr #9040Bernhard KantzTeilnehmerFlexPro Professional supports the following features:
– Updating of preview, object hierarchy and data statistics in the background.
– Parallelizing of computations on multicore processor systems.For these features you have to enable the option “Update objects in the background” (Tools|Options|System Settings).
But not all used algorithms use the parallelizing (e.g. FFT). Generally, the algorithms are parallelized where the data are linear elementwise calculated.
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