Analisis and tools for performance prediction
- Autores
- González, J.A.; León, C.; Piccoli, María Fabiana; Printista, Alicia Marcela; Roda García, José Luis; Rodriguez, C.; Rodríguez, J.M.; Sande Gonzalez, Francisco de
- Año de publicación
- 2001
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- We present an analytical model that extends BSP to cover both oblivious synchronization and group partitioning. There are a few oversimplifications in BSP that make difficult to have accurate predictions. Even if the numbers of individual communication or computation operations in two stages are the same, the actual times for these two stages may differ. These differences are due to the separate nature of the operations or to the particular pattern followed by the messages. Even worse, the assumption that a constant number of machine instructions takes constant time is far from the truth. Current memory hierarchies imply that memory access vary from a few cycles to several thousands. A natural proposal is to associate a different proportionality constant with each basic block, and analogously, to associate different latencies and bandwidths with each “communication block”. Unfortunately, to use this approach implies that the evaluation parameters not only depend on given architecture, but also reflect algorithm characteristics. Such parameter evaluation must be done for every algorithm. This is a heavy task, implying experiment design, timing, statistics, pattern recognition and multi-parameter fitting algorithms. Software support is required. We have developed a compiler that takes as source a C program annotated with complexity formulas and produces as output an instrumented code. The trace files obtained from the execution of the resulting code are analyzed with an interactive interpreter, giving us, among other information, the values of those parameters.
Eje: Programación concurrente
Red de Universidades con Carreras en Informática (RedUNCI) - Materia
-
Ciencias Informáticas
Complexity model
Performance analysis
Performance prediction
Oblivious synchronization
Performance
Concurrent Programming
Tools
Performance profiling - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
.jpg)
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/23310
Ver los metadatos del registro completo
| id |
SEDICI_5c2dcd86c212273c4ab81c75178e8209 |
|---|---|
| oai_identifier_str |
oai:sedici.unlp.edu.ar:10915/23310 |
| network_acronym_str |
SEDICI |
| repository_id_str |
1329 |
| network_name_str |
SEDICI (UNLP) |
| spelling |
Analisis and tools for performance predictionGonzález, J.A.León, C.Piccoli, María FabianaPrintista, Alicia MarcelaRoda García, José LuisRodriguez, C.Rodríguez, J.M.Sande Gonzalez, Francisco deCiencias InformáticasComplexity modelPerformance analysisPerformance predictionOblivious synchronizationPerformanceConcurrent ProgrammingToolsPerformance profilingWe present an analytical model that extends BSP to cover both oblivious synchronization and group partitioning. There are a few oversimplifications in BSP that make difficult to have accurate predictions. Even if the numbers of individual communication or computation operations in two stages are the same, the actual times for these two stages may differ. These differences are due to the separate nature of the operations or to the particular pattern followed by the messages. Even worse, the assumption that a constant number of machine instructions takes constant time is far from the truth. Current memory hierarchies imply that memory access vary from a few cycles to several thousands. A natural proposal is to associate a different proportionality constant with each basic block, and analogously, to associate different latencies and bandwidths with each “communication block”. Unfortunately, to use this approach implies that the evaluation parameters not only depend on given architecture, but also reflect algorithm characteristics. Such parameter evaluation must be done for every algorithm. This is a heavy task, implying experiment design, timing, statistics, pattern recognition and multi-parameter fitting algorithms. Software support is required. We have developed a compiler that takes as source a C program annotated with complexity formulas and produces as output an instrumented code. The trace files obtained from the execution of the resulting code are analyzed with an interactive interpreter, giving us, among other information, the values of those parameters.Eje: Programación concurrenteRed de Universidades con Carreras en Informática (RedUNCI)2001-10info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfhttp://sedici.unlp.edu.ar/handle/10915/23310enginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-10-22T16:36:55Zoai:sedici.unlp.edu.ar:10915/23310Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-10-22 16:36:56.248SEDICI (UNLP) - Universidad Nacional de La Platafalse |
| dc.title.none.fl_str_mv |
Analisis and tools for performance prediction |
| title |
Analisis and tools for performance prediction |
| spellingShingle |
Analisis and tools for performance prediction González, J.A. Ciencias Informáticas Complexity model Performance analysis Performance prediction Oblivious synchronization Performance Concurrent Programming Tools Performance profiling |
| title_short |
Analisis and tools for performance prediction |
| title_full |
Analisis and tools for performance prediction |
| title_fullStr |
Analisis and tools for performance prediction |
| title_full_unstemmed |
Analisis and tools for performance prediction |
| title_sort |
Analisis and tools for performance prediction |
| dc.creator.none.fl_str_mv |
González, J.A. León, C. Piccoli, María Fabiana Printista, Alicia Marcela Roda García, José Luis Rodriguez, C. Rodríguez, J.M. Sande Gonzalez, Francisco de |
| author |
González, J.A. |
| author_facet |
González, J.A. León, C. Piccoli, María Fabiana Printista, Alicia Marcela Roda García, José Luis Rodriguez, C. Rodríguez, J.M. Sande Gonzalez, Francisco de |
| author_role |
author |
| author2 |
León, C. Piccoli, María Fabiana Printista, Alicia Marcela Roda García, José Luis Rodriguez, C. Rodríguez, J.M. Sande Gonzalez, Francisco de |
| author2_role |
author author author author author author author |
| dc.subject.none.fl_str_mv |
Ciencias Informáticas Complexity model Performance analysis Performance prediction Oblivious synchronization Performance Concurrent Programming Tools Performance profiling |
| topic |
Ciencias Informáticas Complexity model Performance analysis Performance prediction Oblivious synchronization Performance Concurrent Programming Tools Performance profiling |
| dc.description.none.fl_txt_mv |
We present an analytical model that extends BSP to cover both oblivious synchronization and group partitioning. There are a few oversimplifications in BSP that make difficult to have accurate predictions. Even if the numbers of individual communication or computation operations in two stages are the same, the actual times for these two stages may differ. These differences are due to the separate nature of the operations or to the particular pattern followed by the messages. Even worse, the assumption that a constant number of machine instructions takes constant time is far from the truth. Current memory hierarchies imply that memory access vary from a few cycles to several thousands. A natural proposal is to associate a different proportionality constant with each basic block, and analogously, to associate different latencies and bandwidths with each “communication block”. Unfortunately, to use this approach implies that the evaluation parameters not only depend on given architecture, but also reflect algorithm characteristics. Such parameter evaluation must be done for every algorithm. This is a heavy task, implying experiment design, timing, statistics, pattern recognition and multi-parameter fitting algorithms. Software support is required. We have developed a compiler that takes as source a C program annotated with complexity formulas and produces as output an instrumented code. The trace files obtained from the execution of the resulting code are analyzed with an interactive interpreter, giving us, among other information, the values of those parameters. Eje: Programación concurrente Red de Universidades con Carreras en Informática (RedUNCI) |
| description |
We present an analytical model that extends BSP to cover both oblivious synchronization and group partitioning. There are a few oversimplifications in BSP that make difficult to have accurate predictions. Even if the numbers of individual communication or computation operations in two stages are the same, the actual times for these two stages may differ. These differences are due to the separate nature of the operations or to the particular pattern followed by the messages. Even worse, the assumption that a constant number of machine instructions takes constant time is far from the truth. Current memory hierarchies imply that memory access vary from a few cycles to several thousands. A natural proposal is to associate a different proportionality constant with each basic block, and analogously, to associate different latencies and bandwidths with each “communication block”. Unfortunately, to use this approach implies that the evaluation parameters not only depend on given architecture, but also reflect algorithm characteristics. Such parameter evaluation must be done for every algorithm. This is a heavy task, implying experiment design, timing, statistics, pattern recognition and multi-parameter fitting algorithms. Software support is required. We have developed a compiler that takes as source a C program annotated with complexity formulas and produces as output an instrumented code. The trace files obtained from the execution of the resulting code are analyzed with an interactive interpreter, giving us, among other information, the values of those parameters. |
| publishDate |
2001 |
| dc.date.none.fl_str_mv |
2001-10 |
| dc.type.none.fl_str_mv |
info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion Objeto de conferencia http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
| format |
conferenceObject |
| status_str |
publishedVersion |
| dc.identifier.none.fl_str_mv |
http://sedici.unlp.edu.ar/handle/10915/23310 |
| url |
http://sedici.unlp.edu.ar/handle/10915/23310 |
| dc.language.none.fl_str_mv |
eng |
| language |
eng |
| dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/2.5/ar/ Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) |
| eu_rights_str_mv |
openAccess |
| rights_invalid_str_mv |
http://creativecommons.org/licenses/by-nc-sa/2.5/ar/ Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5) |
| dc.format.none.fl_str_mv |
application/pdf |
| dc.source.none.fl_str_mv |
reponame:SEDICI (UNLP) instname:Universidad Nacional de La Plata instacron:UNLP |
| reponame_str |
SEDICI (UNLP) |
| collection |
SEDICI (UNLP) |
| instname_str |
Universidad Nacional de La Plata |
| instacron_str |
UNLP |
| institution |
UNLP |
| repository.name.fl_str_mv |
SEDICI (UNLP) - Universidad Nacional de La Plata |
| repository.mail.fl_str_mv |
alira@sedici.unlp.edu.ar |
| _version_ |
1846782828560252928 |
| score |
12.982451 |