Layer-Centric Memory Reuse and Data Migration for Extreme-Scale Deep Learning on Many-Core 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...

Adding shared memory parallelism to FLASH for many-core architectures

In this paper we discuss evolutionary changes to FLASH to enable enhanced applications to run efficiently on both the current generation BG/P and the next generation BG/Q. We motivate the need for change by discussing current FLASH applications and the challenges they are facing on today’s architectures. Our solution to current challenges with a view to the next generation is mixed-mode MPI+Ope...

Generating Code and Memory Buffers to Reorganize Data on Many-core Architectures

The dataflow programming model has shown to be a relevant approach to efficiently run massively parallel applications over many-core architectures. In this model, some particular builtin agents are in charge of data reorganizations between user agents. Such agents can Split, Join and Duplicate data onto their communication ports. They are widely used in signal processing for example. These syst...

Many Core Hardware Architectures