MEDIS 2015 - 1st IEEE International Workshop on Mobile and Embedded Devices Integrated Supercomputing

Mobile and Embedded platforms are used everywhere today. Researchers and system designers provide platforms with more features for parallelization such as multicore architecture, integrated pipelining, independent distributed and shared cache, per clock cycle execution and on the other hand, they work on software architecture to support aforementioned hardware, compilers and code generators, mobile operating systems with ability of serving concurrent processes and threads. GPGPU is currently the dominant platform for supercomputing. The challenge is becoming more exciting when GPGPU chips with high number of simple cores are embedded in SoC, facilitating developers to increase computational speed on mobile platforms extensively.
MEDIS Workshop is aiming to collect and choose high quality papers in the filed of mobile supercomputing and provide a platform for researchers and scientists to discuss about future generation of ultra dense multicore mobile and embedded platforms used in computationally heavy applications. Such platforms will be used in Cognitive and Semantic Robotics, ubiquities Computing, and they help improving the quality of life in general. Papers are encouraged to present innovative ideas in software or hardware design and development for parallel computing used in mobile platforms.
MEDIS 2015 fosters the following complementary objectives:
i. Inquiring on theory and practice of Parallel programming and supercomputing, especially for mobile and embedded devices.
ii. Exploring new mobile and embedded hardware architectures and kits facilitating massive parallelization in small scale.
iii. Deploying new technologies in the fields of Parallel programming, ultra dense supercomputing, and mobile GPGPU based computing.
Topics of interest include but not limited to:
Parallel Computation for Embedded systems
Design and Development of Parallel and Multicore Embedded platforms
Mobile Supercomputing
GPGPU SoC
Hardware realization of parallel algorithms for mobile devices
Distributed mobile cloud
Embedded Supercomputing
Tegra Jetson K1 GPGPU programming
CUDA and MAGMA on mobile
massive parallelization schemes
Parallel Algorithms
Mobile Supercomputing Applications
Network Bottleneck for Massive Parallelization
Clouds and Distributed Computing
Data Analytics
Visualization and Storage
Performance
System Software for Parallel machines