- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
Link Copied
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
Hello kchen3,
HPL stands for High-Performance Linpack. It's a widely-used HPC benchmark available free from Netlib. The Top500 list of most powerful HPC systems uses HPL as its metric.
Parallelefficiency = T1 / (TN * NP) where T1 is the runtime on one processor, TN is the runtime on N processors, and NP is the number of processors. For example, an application thattakes 100 seconds to execute in serial but only 10 seconds to execute in parallel on 10 processors achieves 100% parallel efficiency. An application thattakes 100 seconds to execute in serial but 50 seconds to execute in parallel on 10 processors achieves only20% parallel efficiency.
Best regards,
Henry
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
Yes, Thanks Henry for your wonderful explaination.
Do you know how it reach so high efficiency?
thanks
Stan
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
Economies of scale ?
There must be more advantages to "Bigness" than linear performance improvement.
What other features of scale does your design exploit. Higher capacity utilizaion ? Decreasing cost per unit throgh automation of
maintenance functions ?
- Mark as New
- Bookmark
- Subscribe
- Mute
- Subscribe to RSS Feed
- Permalink
- Report Inappropriate Content
rwilkins@usinter.net wrote:
Linear speed-up and scale-up alone is inadequate.
rwilkens -
In some cases, these two items are enough. Sure, the pencil pushers and accountants are going to be looking at price-performance. However, the scientists that use the equipment will be looking just at performance. From my experience, if you can provide a machine that will allow their application to run twice as fast (or with a data set twice the size) when you double the number of processors, you will be their hero. Assuming that they have applications or data sets that can fill the larger machine, which really isn't as uncommon as that may sound.
So, CAS may be envious of the Thunder efficiency and look to be upgrading their hardware in order to achieve a similar measure. That is, if there is a need for the better efficiency from the users of the system. If the system is serving the needs of the clients at CAS, there would be no need to invest any resources to improve the already pretty high efficiency.
--clay
![](/skins/images/872293744008A34B36F8ABF94A46CC66/responsive_peak/images/icon_anonymous_message.png)
- Subscribe to RSS Feed
- Mark Topic as New
- Mark Topic as Read
- Float this Topic for Current User
- Bookmark
- Subscribe
- Printer Friendly Page