P Russo's scientific contributions

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Publications (4)

Figure 1. Error recovery example.
Figure 5. AST transformation of ill-formed C++ code preparing it for...
Figure 6. A complex example of dynamic expression. Usually the dynamic...
Figure 7. Error recovery example.
+1 Figure 8. ROOT core.
Cling – The New Interactive Interpreter for ROOT 6
Conference Paper
Full-text available
  • May 2012
Cling is an interactive C++ interpreter, built on top of Clang and LLVM compiler infrastructure. Like its predecessor Cint, Cling realizes the read-print-evaluate-loop concept, in order to leverage rapid application development. Implemented as a small extension to LLVM and Clang, the interpreter reuses their strengths such as the praised concise an...
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Fig. 1. Most frequent approach to start using ROOT.
Fig. 2. Example of typical usage of ROOT.
Fig. 3. Transient/persistent conversion in ROOT.
Fig. 4. Automatic splitting of a container of objects.
+4 Fig. 5. Column-wise layout of TTree data in memory buffers.
ROOT - A C++ Framework for Petabyte Data Storage, Statistical Analysis and Visualization
Article
Full-text available
  • Jun 2011
A new stable version ("production version") v5.28.00 of ROOT [1] has been published [2]. It features several major improvements in many areas, most noteworthy data storage performance as well as statistics and graphics features. Some of these improvements have already been predicted in the original publication Antcheva et al. (2009) [3]. This versi...
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Figure 1: Streamers in ROOT version 0.90
Figure 2: Hand coded schema evolution 2.2. Automatic Schema Evolution...
Figure 3: Column-wise storage 
Support For Significant Evolutions of the User Data Model In ROOT Files
Article
Full-text available
  • Apr 2010
One of the main strengths of ROOT input and output (I/O) is its inherent support for schema evolution. Two distinct modes are supported, one manual via a hand coded streamer function and one fully automatic via the ROOT StreamerInfo. One draw back of the streamer functions is that they are not usable by TTree objects in split mode. Until now, the u...
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Developments in ROOT I/O and trees
Article
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  • Jul 2008
For the last several months the main focus of development in the ROOT I/O package has been code consolidation and performance improvements. We introduced a new pre-fetch mechanism to minimize the number of transactions between client and server, hence reducing the effect of latency on the time it takes to read a file both locally and over wide are...
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Citations

... The need to reconcile high performance with fast development has led to the development of a C ++ interpreter [8] that provides the convenience of a read-eval-print-loop (REPL) interactive experience, also known as programming shell, that supports just-in-time compilation, and allows the use of the same programming language for compiled and interpreted code. The same analysis framework ROOT [9,10] can then be used with compiled code and interactively. ...
Reference: Potential of the Julia programming language for high energy physics computing
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... After all jobs have finished processing of their respective ROG files, merging the resulting outputs from storage elements is done in the second step by a second manger which produce a global dose file of about 36 MB. This latter is explored with ROOT in the last step to produce different dose profiles [11]- [13]. ...
Reference: editor in chief,+1001-Final
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... With this information, N ch pseudo-particles were generated in each event, where each psuedo-particle had a transverse momentum which obeyed the p T spectra reported by ALICE [7,12]. The information of all events generated with the toy MC was stored as a columnar dataset (TTree) using ROOT [19]. Figure 2 displays the mean transverse momentum as a function of the average charged-particle multiplicity density in pp collisions at √ s = 5.02, 7 and 13 TeV. ...
Reference: Extraction of multiparton interactions from ALICE pp collisions data using machine learning
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