Add to ORKGInternational audienceIn this paper, we describe a data-centric version-based approach to extending the task dataflow model with new access types that provide speculation capabilities to applications. We further describe the performance benefits of such a model using two scenarios that model realistic applications ; the parallelization of a finite-state machine and Monte-Carlo simulations
We propose the concept of Speculative Execution for Visual Analytics and discuss its effectiveness f...
Distributed dataflow systems such as Apache Spark and Apache Flink are used to derive new insights f...
Abstract—The FSM-SADF model of computation allows to find a tight bound on the throughput of firm re...
Abstract—We argue that speculation leads to increased parallelism in the coarse-grain dataflow parad...
We argue that speculation leads to increased parallelism in the coarse-grain dataflow paradigm. To d...
Task-based programming models have demonstrated their efficiency in the development of scientific ap...
Parallelism is key for designing and implementing high-performance data analytics on modern processo...
International audienceWhile task-based programming models allow expressing the parallelism of algori...
International audienceDataflow Models of Computation (MoCs) have proven efficient means for modeling...
This paper focuses on the problem of how to find and effectively exploit speculative thread-level pa...
Effectively utilizing available parallelism is becoming harder and harder as systems evolve to many-...
This paper focuses on the problem of how to find and effectively exploit speculative thread-level pa...
Exploiting potential thread-level parallelism (TLP) is becoming the key factor to improving performa...
Speculative service implies that a client's request for a document is serviced by sending, in additi...
This article presents an innovative runtime support for speculative parallel processing of discrete ...
We propose the concept of Speculative Execution for Visual Analytics and discuss its effectiveness f...
Distributed dataflow systems such as Apache Spark and Apache Flink are used to derive new insights f...
Abstract—The FSM-SADF model of computation allows to find a tight bound on the throughput of firm re...
Abstract—We argue that speculation leads to increased parallelism in the coarse-grain dataflow parad...
We argue that speculation leads to increased parallelism in the coarse-grain dataflow paradigm. To d...
Task-based programming models have demonstrated their efficiency in the development of scientific ap...
Parallelism is key for designing and implementing high-performance data analytics on modern processo...
International audienceWhile task-based programming models allow expressing the parallelism of algori...
International audienceDataflow Models of Computation (MoCs) have proven efficient means for modeling...
This paper focuses on the problem of how to find and effectively exploit speculative thread-level pa...
Effectively utilizing available parallelism is becoming harder and harder as systems evolve to many-...
This paper focuses on the problem of how to find and effectively exploit speculative thread-level pa...
Exploiting potential thread-level parallelism (TLP) is becoming the key factor to improving performa...
Speculative service implies that a client's request for a document is serviced by sending, in additi...
This article presents an innovative runtime support for speculative parallel processing of discrete ...
We propose the concept of Speculative Execution for Visual Analytics and discuss its effectiveness f...
Distributed dataflow systems such as Apache Spark and Apache Flink are used to derive new insights f...
Abstract—The FSM-SADF model of computation allows to find a tight bound on the throughput of firm re...