We address the problem of providing support for executing single streaming applications implemented as a pipeline of stages that run on heterogeneous chips comprised of several cores and one on-chip GPU. In this paper, we mainly focus on the API that allows the user to specify the type of parallelism exploited by each pipeline stage running on the multicore CPU, the mapping of the pipeline stages to the devices (GPU or CPU), and the number of active threads. We use a real streaming application as a case of study to illustrate the experimental results that can be obtained with this API. With this example, we evaluate how the different parameter values affect the performance and energy efficiency of a heterogenous on-chip process...
Abstract. Stream languages explicitly describe fork-join and pipeline parallelism, offering a powerf...
Computer engineers are continually faced with the task of translating improvements in fabrication pr...
Graphic processing units (GPUs) as hardware platforms have been gaining popularity in general purpos...
Heterogeneous processing systems have become the industry standard in almost every segment of the co...
The trend of increasing performance by parallelism is followed by the adoption of heterogeneous syst...
As many-core accelerators keep integrating more processing units, it becomes increasingly more diffi...
The StreamIt programming model has been proposed to exploit parallelism in streaming applications ...
The rise of many-core processor architectures in the market answers to a constantly growing need of ...
Over the past two decades, microprocessor manufacturers have typically relied on wider issue widths ...
Streaming processing is an important technology that finds applications in networking, multimedia, s...
Software pipelines permit the decomposition of a repetitive sequential process into a succession of ...
We describe an efficient and scalable code generation framework that automatically maps general purp...
The stream processing paradigm is used in several scientific and enterprise applications in order to...
In the last decade, we have seen a transition from single-core to manycore in computer architectures...
The StreamIt programming model has been proposed to exploit parallelism in streaming applications ...
Abstract. Stream languages explicitly describe fork-join and pipeline parallelism, offering a powerf...
Computer engineers are continually faced with the task of translating improvements in fabrication pr...
Graphic processing units (GPUs) as hardware platforms have been gaining popularity in general purpos...
Heterogeneous processing systems have become the industry standard in almost every segment of the co...
The trend of increasing performance by parallelism is followed by the adoption of heterogeneous syst...
As many-core accelerators keep integrating more processing units, it becomes increasingly more diffi...
The StreamIt programming model has been proposed to exploit parallelism in streaming applications ...
The rise of many-core processor architectures in the market answers to a constantly growing need of ...
Over the past two decades, microprocessor manufacturers have typically relied on wider issue widths ...
Streaming processing is an important technology that finds applications in networking, multimedia, s...
Software pipelines permit the decomposition of a repetitive sequential process into a succession of ...
We describe an efficient and scalable code generation framework that automatically maps general purp...
The stream processing paradigm is used in several scientific and enterprise applications in order to...
In the last decade, we have seen a transition from single-core to manycore in computer architectures...
The StreamIt programming model has been proposed to exploit parallelism in streaming applications ...
Abstract. Stream languages explicitly describe fork-join and pipeline parallelism, offering a powerf...
Computer engineers are continually faced with the task of translating improvements in fabrication pr...
Graphic processing units (GPUs) as hardware platforms have been gaining popularity in general purpos...