Papers by Oscar Quinteros
Resumen Sobre datos de exámenes rendidos y aprobados de las materias del Ciclo Común de Articulac... more Resumen Sobre datos de exámenes rendidos y aprobados de las materias del Ciclo Común de Articulación (CCA) de las carreras de Ingenieŕıa de la Facultad de Tecnoloǵıa y Ciencias Aplicadas, se propone conformar la vista minable apropiada para la aplicación de métodos de mineŕıa de secuencias temporales, como parte de en un proyecto de extracción de conocimiento. El proceso de elaboración de esta vista minable se lleva a cabo siguiendo las actividades de la fase de selección y preparación de datos, según la metodoloǵıa CRISP-DM. Una vez definidos los elementos de la secuencia, Identificador, Tiempo y Evento, se genera una vista minable y se realiza un estudio de frecuencias en las secuencias de aprobación de materias.
This practical tutorial introduces the features available in Haskell for writing parallel and con... more This practical tutorial introduces the features available in Haskell for writing parallel and concurrent programs. We first describe how to write semi-explicit parallel programs by using annotations to express opportunities for parallelism and to help control the granularity of parallelism for effective execution on modern operating systems and processors. We then describe the mechanisms provided by Haskell for writing explicitly parallel programs with a focus on the use of software transactional memory to help share information between threads. Finally, we show how nested data parallelism can be used to write deterministically parallel programs which allows programmers to use rich data types in data parallel programs which are automatically transformed into flat data parallel versions for efficient execution on multi-core processors.
This practical tutorial introduces the features available in
Haskell for writing parallel and con... more This practical tutorial introduces the features available in
Haskell for writing parallel and concurrent programs. We first describe
how to write semi-explicit parallel programs by using annotations to express
opportunities for parallelism and to help control the granularity of
parallelism for effective execution on modern operating systems and processors.
We then describe the mechanisms provided by Haskell for writing
explicitly parallel programs with a focus on the use of software transactional
memory to help share information between threads. Finally, we
show how nested data parallelism can be used to write deterministically
parallel programs which allows programmers to use rich data types in
data parallel programs which are automatically transformed into flat
data parallel versions for efficient execution on multi-core processors.
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Papers by Oscar Quinteros
Haskell for writing parallel and concurrent programs. We first describe
how to write semi-explicit parallel programs by using annotations to express
opportunities for parallelism and to help control the granularity of
parallelism for effective execution on modern operating systems and processors.
We then describe the mechanisms provided by Haskell for writing
explicitly parallel programs with a focus on the use of software transactional
memory to help share information between threads. Finally, we
show how nested data parallelism can be used to write deterministically
parallel programs which allows programmers to use rich data types in
data parallel programs which are automatically transformed into flat
data parallel versions for efficient execution on multi-core processors.
Haskell for writing parallel and concurrent programs. We first describe
how to write semi-explicit parallel programs by using annotations to express
opportunities for parallelism and to help control the granularity of
parallelism for effective execution on modern operating systems and processors.
We then describe the mechanisms provided by Haskell for writing
explicitly parallel programs with a focus on the use of software transactional
memory to help share information between threads. Finally, we
show how nested data parallelism can be used to write deterministically
parallel programs which allows programmers to use rich data types in
data parallel programs which are automatically transformed into flat
data parallel versions for efficient execution on multi-core processors.