A Methodology for Profiling and Partitioning Stream Programs on Many-core Architectures

A Methodology for Profiling and Partitioning Stream Programs on Many-core Architectures

Maximizing the data throughput is a very common implementation objective for several streaming applications. Such task is particularly challenging for implementations based on many-core and multi-core target platforms because, in general, it implies tackling several NPcomplete combinatorial problems. Moreover, an efficient design space exploration requires an accurate evaluation on the basis of...

Many-Task Computing on Many-Core Architectures

Many-Task Computing (MTC) is a common scenario for multiple parallel systems, such as cluster, grids, cloud and supercomputers, but it is not so popular in shared memory parallel processors. In this sense and given the spectacular growth in performance and in number of cores integrated in many-core architectures, the study of MTC on such architectures is becoming more and more relevant. In this...

Algorithms and Framework for Energy Efficient Parallel Stream Computing on Many-Core Architectures

The rise of many-core processor architectures in the market answers to a constantly growing need of processing power to solve more and more challenging problems such as the ones in computing for big data. Fast computation is more and more limited by the very high power required and the management of the considerable heat produced. Many programming models compete to take profit of many-core arch...

A polyphase filter for many-core architectures

In this article we discuss our implementation of a polyphase filter for real-time data processing in radio astronomy. The polyphase filter is a standard tool in digital signal processing and as such a well established algorithm. We describe in detail our implementation of the polyphase filter algorithm and its behaviour on three generations of NVIDIA GPU cards (Fermi, Kepler, Maxwell), on the I...

Many Core Hardware Architectures