Optimization of Selected Remote Sensing Algorithms for Many-Core Architectures

Efficient Primitives and Algorithms for Many-core architectures

OF THE DISSERTATION Efficient Primitives and Algorithms for Many-core architectures Graphics Processing Units (GPUs) are a fast evolving architecture. Over the last decade their programmability has been harnessed to solve non-graphics tasks—in many cases at a huge performance advantage to CPUs. Unlike CPUs, GPUs have always been a highly parallel architecture—thousands of lightweight execution ...

Many Core Hardware Architectures

Memory Optimization in Codelet Execution Model on Many-core Architectures

The upcoming exa-scale era requires a parallel program execution model capable of achieving scalability, productivity, energy efficiency, and resiliency. The codelet model is a fine-grained dataflow-inspired execution model which is the focus of several tera-scale and exa-scale studies such as DARPA’s UHPC, DOE’s X-Stack, and the European TERAFLUX projects. Current codelet implementations aim t...

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...

Declarative Programming Techniques for Many-Core Architectures

Future manycore architectures are likely to have heterogeneous computing resources which will include conventional CPUs as well as variants of today’s GPUs and reconfigurable logic like FPGAs. Many of the techniques that the reconfigurable computing community has championed will find new applications in mainstream applications. One challenge posed by such manycore architectures is the requireme...