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Gaurav Mitra

Publications and source records attributed to Gaurav Mitra.

2 recordsLinked to original sources

A Coarse-Grained Simulation Model for Self-Assembly of Liquid Droplets Featuring Explicit Mobile Binders

Colloidal particles with mobile binding molecules constitute a powerful platform for probing the physics of self-assembly. Binding molecules are free to diffuse and rearrange on the surface, giving rise to spontaneous control over the number of droplet-droplet bonds, i.e., valence, as a function of the concentration of binders. This type of valence control has been realized experimentally by tuning the interaction strength between DNA-coated emulsion droplets. Optimizing for valence two yields droplet polymer chains, termed `colloidomers', which have recently been used to probe the physics of folding. To understand the underlying self-assembly mechanisms, here we present a coarse-grained molecular dynamics (CGMD) model to study the self-assembly of this class of systems using explicit representations of mobile binding sites. We explore how valence of assembled structures can be tuned through kinetic control in the strong binding limit. More specifically, we optimize experimental control parameters to obtain the highest yield of long linear colloidomer chains. Subsequently tuning the dynamics of binding and unbinding via a temperature-dependent model allows us to observe the heptamer chain collapse into all possible rigid structures, in good agreement with recent folding experiments. Our CGMD platform and dynamic bonding model (implemented as an open-source custom plugin to HOOMD-Blue) reveal the molecular features governing the binding patch size and valence control, and opens the study of pathways in colloidomer folding. This model can therefore guide programmable design in experiments.

cond-mat.soft

Programming the Adapteva Epiphany 64-core Network-on-chip Coprocessor

In the construction of exascale computing systems energy efficiency and power consumption are two of the major challenges. Low-power high performance embedded systems are of increasing interest as building blocks for large scale high- performance systems. However, extracting maximum performance out of such systems presents many challenges. Various aspects from the hardware architecture to the programming models used need to be explored. The Epiphany architecture integrates low-power RISC cores on a 2D mesh network and promises up to 70 GFLOPS/Watt of processing efficiency. However, with just 32 KB of memory per eCore for storing both data and code, and only low level inter-core communication support, programming the Epiphany system presents several challenges. In this paper we evaluate the performance of the Epiphany system for a variety of basic compute and communication operations. Guided by this data we explore strategies for implementing scientific applications on memory constrained low-powered devices such as the Epiphany. With future systems expected to house thousands of cores in a single chip, the merits of such architectures as a path to exascale is compared to other competing systems.

cs.AR