- Timestamp:
- Feb 15, 2010, 2:32:46 PM (15 years ago)
- Location:
- anr
- Files:
-
- 3 edited
Legend:
- Unmodified
- Added
- Removed
-
anr/anr.bib
r135 r174 620 620 year = {2001}, 621 621 } 622 @INPROCEEDINGS{FP:96 623 ,AUTHOR = "Paul Feautrier" 624 ,TITLE = "Automatic Parallelization in the Polytope Model" 625 ,BOOKTITLE = "The Data-Parallel Programming Model" 626 ,YEAR = 1996 627 ,EDITOR = "Guy-Ren\'e Perrin and Alain Darte" 628 ,PAGES = "79--103" 629 ,VOLUME = "LNCS 1132" 630 ,PUBLISHER = "Springer" 631 } 632 633 @book{DRV:2000, 634 author={Alain Darte and Yves Robert and Fr\'ed\'eric Vivien}, 635 title={Scheduling and automatic Parallelization}, 636 publisher={Birkh\"auser}, year=2000 637 } -
anr/section-3.1.tex
r134 r174 166 166 167 167 \subsubsection{Automatic Parallelization} 168 % FIXME:LIP FIXME:PF FIXME:CA169 % Paul je ne suis pas sur que ce soit vraiment un etat de l'art170 % Christophe, ce que tu m'avais envoye se trouve dans obsolete/body.tex171 %\mustbecompleted{172 %Hardware is inherently parallel. On the other hand, high level languages,173 %like C or Fortran, are abstractions of the processors of the 1970s, and174 %hence are sequential. One of the aims of an HLS tool is therefore to175 %extract hidden parallelism from the source program, and to infer enough176 %hardware operators for its efficient exploitation.177 %\\178 %Present day HLS tools search for parallelism in linear pieces of code179 %acting only on scalars -- the so-called basic blocs. On the other hand,180 %it is well known that most programs, especially in the fields of signal181 %processing and image processing, spend most of their time executing loops182 %acting on arrays. Efficient use of the large amount of hardware available183 %in the next generation of FPGA chips necessitates parallelism far beyond184 %what can be extracted from basic blocs only.185 186 %The Compsys team of LIP has built an automatic parallelizer, Syntol, which187 %handle restricted C programs -- the well known polyhedral model --,188 %computes dependences and build a symbolic schedule. The schedule is189 %a specification for a parallel program. The parallelism itself can be190 %expressed in several ways: as a system of threads, or as data-parallel191 %operations, or as a pipeline. In the context of the COACH project, one192 %of the task will be to decide which form of parallelism is best suited193 %to hardware, and how to convey the results of Syntol to the actual194 %synthesis tools. One of the advantages of this approach is that the195 %resulting degree of parallelism can be easilly controlled, e.g. by196 %adjusting the number of threads, as a mean of exploring the197 %area / performance tradeoff of the resulting design.198 199 %Another point is that potentially parallel programs necessarily involve200 %arrays: two operations which write to the same location must be executed201 %in sequence. In synthesis, arrays translate to memory. However, in FPGAs,202 %the amount of on-chip memory is limited, and access to an external memory203 %has a high time penalty. Hence the importance of reducing the size of204 %temporary arrays to the minimum necessary to support the requested degree205 %of parallelism. Compsys has developped a stand-alone tool, Bee, based206 %on research by A. Darte, F. Baray and C. Alias, which can be extended207 %into a memory optimizer for COACH.208 %}209 168 210 169 The problem of compiling sequential programs for parallel computers … … 214 173 the preservation of the program semantics. Most of these transformations 215 174 just reorder the operations of the program; some of them modify its 216 data structures. D pendences (exact or conservative) are checked to guarantee175 data structures. Dependences (exact or conservative) are checked to guarantee 217 176 the legality of the transformation. 218 177 … … 221 180 which interact in a complicated way. More recently, it has been noticed 222 181 that all of these are just changes of basis in the iteration domain of 223 the program. This has lead to the invention of the polyhedral model, in 224 which the combination of two transformation is simply a matrix product. 225 226 As a side effect, it has been observed that the polytope model is a useful 182 the program. This has lead to the introduction of the polyhedral model, 183 \cite{FP:96,DRV:2000} in which the combination of two transformation is 184 simply a matrix product. 185 186 Since hardware is inherently parallel, finding parallelism in sequential 187 programs in an important prerequisite for HLS. The large FPGA chips of 188 today can accomodate much more parallelism than is available in basic blocks. 189 The polyhedral model is the ideal tool for finding more parallelism in 190 loops. 191 192 As a side effect, it has been observed that the polyhedral model is a useful 227 193 tool for many other optimization, like memory reduction and locality 228 194 improvement. Another point is -
anr/section-7.tex
r167 r174 46 46 professor at ENS Lyon (Paul Feautrier) and a research associate 47 47 (CR2) at INRIA Rh\^one-Alpes (Christophe Alias). The non-permanent 48 person al required is a PhD student that will work on network process48 personel required is a PhD student that will work on network process 49 49 generation from polyhedral loops, then on extensions to 50 50 non-polyhedral loops. We are looking for a student with both … … 53 53 a working implementation. 54 54 \parlf 55 The table below summarizes the \hommemois in man-monthsby55 The table below summarizes the \hommemois by 56 56 deliverables and tasks for both permanent and non-permanent 57 57 personnels. The non-permanent personnels costs represent 23\% of
Note: See TracChangeset
for help on using the changeset viewer.