Automatic Compilation of MATLAB Programs for Synergistic Execution on Heterogeneous Processors

MATLAB is an array language, initially popular for rapid prototyping, but is now being increasingly used to develop production code for numerical and scientific applications. Typical MATLAB programs have abundant data parallelism. These programs also have control flow dominated scalar regions that have an impact on the program's execution time. Today's computer systems have tremendous computing power in the form of traditional CPU cores and throughput oriented accelerators such as graphics processing units(GPUs). Thus, an approach that maps the control flow dominated regions to the CPU and the data parallel regions to the GPU can significantly improve program performance. In this paper, we present the design and implementation of MEGHA, a compiler that automatically compiles MATLAB programs to enable synergistic execution on heterogeneous processors. Our solution is fully automated and does not require programmer input for identifying data parallel regions. We propose a set of compiler optimizations tailored for MATLAB. Our compiler identifies data parallel regions of the program and composes them into kernels. The problem of combining statements into kernels is formulated as a constrained graph clustering problem. Heuristics are presented to map identified kernels to either the CPU or GPU so that kernel execution on the CPU and the GPU happens synergistically and the amount of data transfer needed is minimized. In order to ensure required data movement for dependencies across basic blocks, we propose a data flow analysis and edge splitting strategy. Thus our compiler automatically handles composition of kernels, mapping of kernels to CPU and GPU, scheduling and insertion of required data transfer. The proposed compiler was implemented and experimental evaluation using a set of MATLAB benchmarks shows that our approach achieves a geometric mean speedup of 19.8X for data parallel benchmarks over native execution of MATLAB.

Multi-agent search using?sensors with heterogeneous capabilities

In this thesis we address the problem of multi-agent search. We formulate two deploy and search strategies based on optimal deployment of agents in search space so as to maximize the search effectiveness in a single step. We show that a variation of centroidal Voronoi configuration is the optimal deployment. When the agents have sensors with different capabilities, the problem will be heterogeneous in nature. We introduce a new concept namely, generalized Voronoi partition in order to formulate and solve the heterogeneous multi-agent search problem. We address a few theoretical issues such as optimality of deployment, convergence and spatial distributedness of the control law and the search strategies. Simulation experiments are carried out to compare performances of the proposed strategies with a few simple search strategies.

Mesoscopics nanoscopics and macroscopics materials

At the present time, materials with dimensions in the range of microns to nanometers have become the prime objects of vigorous research activities of all over the world. The possibility of artificially creating novel materials with exotic and tailor made properties that are essential for future development in the frontier areas of electronics, photonics, spintronics etc has generated much interest in the study of these mesoscopic and nanoscopic materials. These materials also have the potential for wide ranging economically viable technological, industrial, engineering and bio-medical applications. They may consist of metals , alloys , ceramics, polymers, composites and biological materials; which are usually assembled at the atomic / molecular level to achieve new properties. Understanding the underlying science and characterization of these new materials with a view of harnessing their exotic properties is the prime focus of the researchers. These Proceedings address these issues relating to mesoscopic, nanoscopic and macroscopic materials.

Effect of strain path change on the evolution of texture and microstructure during rolling of copper and nickel

The effect of strain path change during rolling has been investigated for copper and nickel using X-ray diffraction and electron back scatter diffraction as well as crystal plasticity simulations. Four different strain paths namely: (i) unidirectional rolling; (ii) reverse rolling; (iii) two-step cross rolling and (iv) multi-step cross rolling were employed to decipher the effect of strain path change on the evolution of deformation texture and microstructure. The cross rolled samples showed weaker texture with a prominent Bs {1 1 0}< 1 1 2 > and P(B(ND)) {1 1 0}< 1 1 1 > component in contrast to the unidirectional and reverse rolled samples where strong S {1 2 3}< 6 3 4 > and Cu {1 1 2}< 1 1 1 > components were formed. This was more pronounced for copper samples compared to nickel. The cross rolled samples were characterized by lower anisotropy and Taylor factor as well as less variation in Lankford parameter. Viscoplastic self-consistent simulations indicated that slip activity on higher number of octahedral slip systems can explain the weaker texture as well as reduced anisotropy in the cross rolled samples. (C) 2011 Elsevier B.V. All rights reserved.