This work studies the issues related to dynamic memory management in Data Stream Processing, an emerging paradigm enabling the real-time processing of live data streams. In this paper, we consider two streaming parallel patterns and we discuss different implementation variants related to how dynamic memory is managed. The results show that the standard mechanisms provided by modern C++ are not entirely adequate for maximizing the performance. Instead, the combined use of an efficient general purpose memory allocator, a custom allocator optimized for the pattern considered and a custom variant of the C++ shared pointer mechanism, provides a performance improvement up to 16% on the best case
Stream processing applications compute streams of data and provide insightful results in a timely ma...
Streaming data analysis has recently attracted at-tention in numerous applications including telepho...
The goal of buffer allocation for real-time streaming applications, modeled as dataflow graphs, is t...
This work studies the issues related to dynamic memory management in Data Stream Processing, an emer...
Data Stream Processing is a paradigm enabling the real-time processing of live data streams coming f...
In the stream processing domain, applications are represented by graphs of operators arbitrarily con...
The topic of Data Stream Processing is a recent and highly active research area dealing with the in-...
This paper investigates memory management for real-time multimedia applications running on resource-...
Coherent read misses in shared-memory multiprocessors account for a substantial fraction of executio...
The topic of Data Stream Processing is a recent and highly active research area dealing with the in-...
The growing disparity between processor and memory speeds has caused memory bandwidth to become the ...
Distributed stream-based applications manage large quantities of data and exhibit unique production ...
Memory bandwidth is rapidly becoming the limiting performance factor for many applications, particul...
We describe an approach to elastically scale the per-formance of a data analytics operator that is p...
Buffer allocation for real-time streaming applications, modeled as dataflow graphs, minimizes the to...
Stream processing applications compute streams of data and provide insightful results in a timely ma...
Streaming data analysis has recently attracted at-tention in numerous applications including telepho...
The goal of buffer allocation for real-time streaming applications, modeled as dataflow graphs, is t...
This work studies the issues related to dynamic memory management in Data Stream Processing, an emer...
Data Stream Processing is a paradigm enabling the real-time processing of live data streams coming f...
In the stream processing domain, applications are represented by graphs of operators arbitrarily con...
The topic of Data Stream Processing is a recent and highly active research area dealing with the in-...
This paper investigates memory management for real-time multimedia applications running on resource-...
Coherent read misses in shared-memory multiprocessors account for a substantial fraction of executio...
The topic of Data Stream Processing is a recent and highly active research area dealing with the in-...
The growing disparity between processor and memory speeds has caused memory bandwidth to become the ...
Distributed stream-based applications manage large quantities of data and exhibit unique production ...
Memory bandwidth is rapidly becoming the limiting performance factor for many applications, particul...
We describe an approach to elastically scale the per-formance of a data analytics operator that is p...
Buffer allocation for real-time streaming applications, modeled as dataflow graphs, minimizes the to...
Stream processing applications compute streams of data and provide insightful results in a timely ma...
Streaming data analysis has recently attracted at-tention in numerous applications including telepho...
The goal of buffer allocation for real-time streaming applications, modeled as dataflow graphs, is t...