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Use of variable size array to model the Atlas raw data

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Presentation on theme: "Use of variable size array to model the Atlas raw data"— Presentation transcript:

1 Use of variable size array to model the Atlas raw data
Simona Rolli - TUFTS University R.D. Schaffer - LAL/Orsay Martin Schaller - CERN/Innsbruck Andrea Salvadori - CERN CHEP, Padova, Simona Rolli - TUFTS

2 N N 1 1 1 N Introduction PEvent PEventObjVector PEvtObj
The current ATLAS event data model has been developed for raw data only. The classes providing access to the raw data (through an identifiers-based method) are the following: PEvent PEventObjVector PEvtObj PNode PNode PNode1 DetectorElement Digit implemented as Varray each channel response is organized in digits contained by an object representing the detector element which produced it. N N 1 1 1 N CHEP, Padova, Simona Rolli - TUFTS

3 wafer_id = “barrel / layer 1 / ring 3 / phi sector 5”
Logical Identifiers Hierarchical Identifiers are used to identify sensitive detector elements and read-out channels: the Identifiers are structured according to the logical structure of the detector: layers phi sectors barrel end-cap eta phi Pixel wafer wafer_id pixel_id rings wafer_id = “barrel / layer 1 / ring 3 / phi sector 5” pixel_id = wafer_id + “eta 19 / phi 33” CHEP, Padova, Simona Rolli - TUFTS

4 Logical Identifiers (2)
Identifiers provide a means of mapping detector-related information across domains or data stores: event raw data <-> detector description event raw data <-> calibration/alignment They also provide a means of selecting the information of interest: we have introduced a Range class for Identifier ranges: Pixel wafer eta phi id1 id2 Range(id1, id2) CHEP, Padova, Simona Rolli - TUFTS

5 The Original Model A generalized model ( modeled after the
original model) assumes a further node -PNode4 ( collection of events) -and the following fan out: 300 Pnode3, 10 PNode2, 100 Pnode1, 50 PDigit Server and Local/Remote client: 2*Sun UltraSparcII 399MHz, 512MB RAM - Hitachy RAID ( 25MB/sec) Remote Server : SUN UltraSparc II, 270MHz, 192 MB RAM, Elite23 drives - 9MB/sec. user time ~ 60-80% real time CHEP, Padova, Simona Rolli - TUFTS

6 The Modified Model The Digit class has been moved to be attached to PNode2 (PEvtObj), through VArrays, while the association-based mechanism of navigation is implemented through arrays of references. user time ~ 60-80% real time CHEP, Padova, Simona Rolli - TUFTS

7 The New Model The Pdigit class has been moved to be attached to PNode2 (PEvtObj), through a variable size arrays - SegVArray - The relationship between PNode3/PNode4 and PNode3/PNode2 is through Objy 1-to-many associations. CHEP, Padova, Simona Rolli - TUFTS

8 SegVArray The class SegVArray is an extension of the ooVArray
class ( same interface) : it contains a ooVArray of SVArraySegments, each containing an ooVArray of the objects to be stored. The advantages are that if only some objects are to be read in, only the segments are read that contains these objects ( ooVArray are always fetched as a whole). If a segment of a SegVArray fits onto a page a SegVArray can span several pages without the storage overhead of half page for large objects. Of course there might be poor performances if all the objects are read from the SegVArray ( further level of indirection) - partially overcome with the use of Iterators. CHEP, Padova, Simona Rolli - TUFTS

9 Results user time ~ 15-30% real time CHEP, Padova, 02-10-00
Simona Rolli - TUFTS

10 Conclusions Performances improve when only a few digits are accessed by the application ( true for local access, for remote access -AMS- there is a further constraint from the internal page caching mechanism in Objectivity/DB) Well in the budget requesting at least 1 MB/sec per a standard reconstruction application. The model has been implemented in the real code and we are in the process of testing it with a large volume of data. Further studies needed in order to optimize the use of these type of arrays. CHEP, Padova, Simona Rolli - TUFTS


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