Hari Krishnan

SHARP: a distributed, GPU-based ptychographic solver

Ever brighter light sources, fast parallel detectors, and advances in phase retrieval methods, have made ptychography a practical and popular imaging technique. Compared to previous techniques, ptychography provides superior robustness and resolution at the expense of more advanced and time consuming data analysis. By taking advantage of massively parallel architectures, high-throughput processing can expedite this analysis and provide microscopists with immediate feedback. These advances allow real-time imaging at wavelength limited resolution, coupled with a large field of view. Here, we introduce a set of algorithmic and computational methodologies used at the Advanced Light Source, and DOE light sources packaged as a CUDA based software environment named SHARP (this http URL), aimed at providing state-of-the-art high-throughput ptychography reconstructions for the coming era of diffraction limited light sources.

The Deadly Combination of Heat and Humidity in India and Pakistan in Summer 2015

Author(s): Wehner, M; Stone, D; Krishnan, H; Achutarao, K; Castillo, F | Abstract:

Nanosurveyor : a framework for real-time data processing

BackgroundThe ever improving brightness of accelerator based sources is enabling novel observations and discoveries with faster frame rates, larger fields of view, higher resolution, and higher dimensionality.ResultsHere we present an integrated software/algorithmic framework designed to capitalize on high-throughput experiments through efficient kernels, load-balanced workflows, which are scalable in design. We describe the streamlined processing pipeline of ptychography data analysis.ConclusionsThe pipeline provides throughput, compression, and resolution as well as rapid feedback to the microscope operators.

GPU-Based Implementation of Ptycho-ADMM for High Performance X-Ray Imaging

X-ray imaging allows biologists to retrieve the atomic arrangement of proteins and doctors the capability to view broken bones in full detail. In this context, ptychography has risen as a reference imaging technique. It provides resolutions of one billionth of a meter, macroscopic field of view, or the capability to retrieve chemical or magnetic contrast, among other features. The goal is to reconstruct a 2D visualization of a sample from a collection of diffraction patterns generated from the interaction of a light source with the sample. The data collected is typically two orders of magnitude bigger than the final image reconstructed, so high performance solutions are normally desired. One of the latest advances in ptychography imaging is the development of Ptycho-ADMM, a new ptychography reconstruction algorithm based on the Alternating Direction Method of Multipliers (ADMM). Ptycho-ADMM provides faster convergence speed and better quality reconstructions, all while being more resilient to noise in comparison with state-of-the-art methods. The downside of Ptycho-ADMM is that it requires additional computation and a larger memory footprint compared to simpler solutions. In this paper we tackle the computational requirements of Ptycho-ADMM, and design the first high performance multi-GPU solution of the method. We analyze and exploit the parallelism of Ptycho-ADMM to make use of multiple GPU devices. The proposed implementation achieves reconstruction times comparable to other GPU-accelerated high performance solutions, while providing the enhanced reconstruction quality of the Ptycho-ADMM method.

Usability Heuristic Evaluation of Scientific Data Analysis and Visualization Tools

Scientific data analysis and visualization (DAV) tools are a critical component of the software ecosystem. The growth in data volumes in various scientific domains is resulting in technical innovations in DAV tools. Usability of these tools is becoming extremely critical to facilitate next-generation scientific discoveries. Usability heuristics is a widely applied approach to inspect software usability. We expand Nielsen’s heuristics to include two additional criteria: analytical-reasoning and customized-experience to capture the usability dimensions of DAV tools. We evaluated three tools to test the proposed heuristics and demonstrate its fit to DAV tools of varying features. The contribution of our work is threefold: (i) identify DAV usability heuristics, (ii) develop a framework to inspect DAV tools, (iii) conduct a comprehensive evaluation of the usability of selected DAV tools. We also provide a discussion on the heuristics framework for DAV tools and future work.

Towards Exascale: High Performance Visualization and Analytics -Project Status Report

Towards Exascale: High Performance Visualization and Analytics – Project Status Report E. Wes Bethel, David Camp, Hank Childs, Mark Howison, Hari Krishnan, Burlen Loring, J org Meyer, Prabhat, Oliver R ubel, Daniela Ushizima, Gunther Weber University of California, Berkeley, Lawrence Berkeley National Laboratory, Berkeley, CA, USA, DOE 2012 Exascale Research Conference and Workshop April 16–18, 2012 Portland, Oregon