As many-core accelerators keep integrating more processing units, it becomes increasingly more difficult for a parallel application to make effective use of all available resources. An effective way for improving hardware utilization is to exploit spatial and temporal sharing of the heterogeneous processing units by multiplexing computation and communication tasks - a strategy known as heterogeneous streaming. Achieving effective heterogeneous streaming requires carefully partitioning hardware among tasks, and matching the granularity of task parallelism to the resource partition. However, finding the right resource partitioning and task granularity is extremely challenging, because there is a large number of possible solutions and the opti...
The rise of many-core processor architectures in the market answers to a constantly growing need of ...
Emerging computer architectures and advanced computing technologies, such as Intel’s Many Integrated...
The StreamIt programming model has been proposed to exploit parallelism in streaming applications ...
As many-core accelerators keep integrating more processing units, it becomes increasingly more diffi...
Many-core accelerators, as represented by the XeonPhi coprocessors and GPGPUs, allow software to exp...
To help shrink the programmability-performance efficiency gap, we discuss that adaptive runtime syst...
Multi-core processors are now ubiquitous and are widely seen as the most viable means of delivering ...
Stream based languages are a popular approach to expressing parallelism in modern applications. The ...
Computing systems have undergone a fundamental transformation from single core devices to devices wi...
Heterogeneous platforms are mixes of different processing units in a compute node (e.g., CPUs+GPUs, ...
Streaming processing is an important technology that finds applications in networking, multimedia, s...
Heterogeneous computing systems provide high performance and energy efficiency. However, to optimall...
Conference of 9th IEEE International Symposium on Embedded Multicore/Manycore SoCs, MCSoC 2015 ; Con...
The next-generation sequencing instruments enable biological researchers to generate voluminous amou...
The stream processing paradigm is used in several scientific and enterprise applications in order to...
The rise of many-core processor architectures in the market answers to a constantly growing need of ...
Emerging computer architectures and advanced computing technologies, such as Intel’s Many Integrated...
The StreamIt programming model has been proposed to exploit parallelism in streaming applications ...
As many-core accelerators keep integrating more processing units, it becomes increasingly more diffi...
Many-core accelerators, as represented by the XeonPhi coprocessors and GPGPUs, allow software to exp...
To help shrink the programmability-performance efficiency gap, we discuss that adaptive runtime syst...
Multi-core processors are now ubiquitous and are widely seen as the most viable means of delivering ...
Stream based languages are a popular approach to expressing parallelism in modern applications. The ...
Computing systems have undergone a fundamental transformation from single core devices to devices wi...
Heterogeneous platforms are mixes of different processing units in a compute node (e.g., CPUs+GPUs, ...
Streaming processing is an important technology that finds applications in networking, multimedia, s...
Heterogeneous computing systems provide high performance and energy efficiency. However, to optimall...
Conference of 9th IEEE International Symposium on Embedded Multicore/Manycore SoCs, MCSoC 2015 ; Con...
The next-generation sequencing instruments enable biological researchers to generate voluminous amou...
The stream processing paradigm is used in several scientific and enterprise applications in order to...
The rise of many-core processor architectures in the market answers to a constantly growing need of ...
Emerging computer architectures and advanced computing technologies, such as Intel’s Many Integrated...
The StreamIt programming model has been proposed to exploit parallelism in streaming applications ...