Gagan AgrawM, Renato Ferriera, and Joel SMtz. Language extensions and compilation techniques for data intensive computations. In Proceedings of Workshop on Compilers for Parallel Computing, January 2000. Home/Search Document Details and Download
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Compiling Data Intensive Applications with Spatial Coordinates - Ferreira, Agrawal, Jin (2000) (Correct)
.... from hydrodynamics and chemical transport simulations [19] and archives of medical images [1] We are developing a compiler which processes data intensive applications written in a dialect of Java and compiles them for efficient execution on cluster of workstations or distributed memory machines [2, 3, 14]. Our chosen dialect of Java includes data parallel extensions for specifying collection of objects, a parallel for loop, and reduction variables. We extract a set of functions (including subscript functions used for accessing left hand side and right hand side object collections, aggregation ....
.... p) a, c fo, t (lat, long) on o t Return the pixel if it exists Else return null public class SatData public class SatOrigData blocklid] satorigdata; void SatOrigData(RectDomain[1] InputDomain) satorigdata = new block[InputDomain] pixel getData(Point[3] q) Point[1] time = q.get(0) Point[2] p = q.get(1) q.get(2) return satorigdata[time] getData(p) void SatData(RectDomain[1] InputDomain) Sat OrigDat a(Input Domain) pixel getData(Point[3] q) return SatOrigData(q) public class Image implements ....
[Article contains additional citation context not shown here]
Gagan AgrawM, Renato Ferriera, and Joel SMtz. Language extensions and compilation techniques for data intensive computations. In Proceedings of Workshop on Compilers for Parallel Computing, January 2000.
A Middleware for Developing Parallel Data Mining Applications - Jin, Agrawal (2001) (1 citation) Self-citation (Agrawal) (Correct)
....with different parallelization strategies. Finally, we plan to use this middleware as the target for a data parallel compiler, to enable parallel data mining algorithms to be expressed in a high level language. In a separate effort, we have developed a compiler for a data parallel dialect of Java [3, 2, 19]. The compiler generates ADR specification starting from data intensive computations expressed in such a dialect of Java. We plan to extend this compilation effort to express data mining techniques and automatically generate the code for middleware interface. Acknowledgments This work builds on ....
Gagan Agrawal, Renato Ferriera, and Joel Saltz. Language extensions and compilation techniques for data intensive computations. In Proceedings of Workshop on Compilers for Parallel Computing, January 2000.
Advanced Compiler and Runtime Support for Data Intensive.. - Ferreira, Agrawal, Saltz Self-citation (Agrawal Ferreira Saltz) (Correct)
.... studies [18] airplane wake turbulence [19] or flame sweeping through a volume [23] We are developing a compiler which processes data intensive applications written in a dialect of Java and compiles them for efficient execution on cluster of workstations or distributed memory machines [4] [3], 14] For our prototype implementation, we have chosen a dialect of Java with dataparallel extensions based on Titanium [25] The prototype compiler makes extensive use of the existing runtime system ADR (Active Data Repository) 7] 8] 10] for optimizing the resource usage during execution ....
....applications at a much higher level. It becomes the responsibility of the compiler to utilize the services of ADR for memory management, data retrieval and scheduling of processes. We have previously worked on techniques to extract the necessary information from data parallel Java programs [4] [3], 14] We extract a set of functions (including subscript functions used for accessing left hand side and right handside object collections, aggregation functions, and range functions) from the given data intensive loop by using the technique of interprocedural program slicing. In this paper, we ....
[Article contains additional citation context not shown here]
Gagan Agrawal, Renato Ferreira, and Joel Saltz. Language extensions and compilation techniques for data intensive computations. In Proceedings of Workshop on Compilers for Parallel Computing, January 2000.
Compiling Data Intensive Applications with Spatial.. - Ferreira, Agrawal, Jin.. (2000) Self-citation (Agrawal Saltz) (Correct)
.... from hydrodynamics and chemical transport simulations [19] and archives of medical images [1] We are developing a compiler which processes data intensive applications written in a dialect of Java and compiles them for efficient execution on cluster of workstations or distributed memory machines [2, 3, 14]. Our chosen dialect of Java includes data parallel extensions for specifying collection of objects, a parallel for loop, and reduction variables. We extract a set of functions (including subscript functions used for accessing left hand side and right hand side object collections, aggregation ....
.... p) f f Search for the (lat, long) on geodata g f Return the pixel if it exists g f Elsereturn null g g g public class SatData f public class SatOrigData f block[1d] satorigdata # void SatOrigData(RectDomain[1] InputDomain) f satorigdata = new block[InputDomain] # g pixel getData(Point[3] q) f Point[1] time = q.get(0) # Point[2] p = q.get(1) q.get(2) # return satorigdata[time] getData(p) # g g void SatData(RectDomain[1] InputDomain) f SatOrigData(InputDomain) # g pixel getData(Point[3] q) f return SatOrigData(q) # g g public class Image implements Reducinterface ....
[Article contains additional citation context not shown here]
Gagan Agrawal, Renato Ferriera, and Joel Saltz. Language extensions and compilation techniques for data intensive computations. In Proceedings of Workshop on Compilers for Parallel Computing, January 2000.
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