The GLEON Research And PRAGMA Lake Expedition -- GRAPLE -- is a collaborative effort between computer science and lake ecology researchers. It aims to improve our understanding and predictive capacity of the threats to the water quality of our freshwater resources, including climate change. This paper presents GRAPLEr, a distributed computing system used to address the modeling needs of GRAPLE researchers. GRAPLEr integrates and applies overlay virtual network, high-throughput computing, and Web service technologies in a novel way. First, its user-level IP-over-P2P (IPOP) overlay network allows compute and storage resources distributed across independently-administered institutions (including private and public clouds) to be aggregated into a common virtual network, despite the presence of firewalls and network address translators. Second, resources aggregated by the IPOP virtual network run unmodified high-throughput computing middleware (HTCondor) to enable large numbers of model simulations to be executed concurrently across the distributed computing resources. Third, a Web service interface allows end users to submit job requests to the system using client libraries that integrate with the R statistical computing environment. The paper presents the GRAPLEr architecture, describes its implementation and reports on its performance for batches of General Lake Model (GLM) simulations across three cloud infrastructures (University of Florida, CloudLab, and Microsoft Azure).
The NERSC Web Toolkit (NEWT) brings High Performance Computing (HPC) to the web through easy to write web applications. Our work seeks to make HPC resources more accessible and useful to scientists who are more comfortable with the web than they are with command line interfaces. The effort required to get a fully functioning web application is decreasing, thanks to Web 2.0 standards and protocols such as AJAX, HTML5, JSON and REST. We believe HPC can speak the same language as the web, by leveraging these technologies to interface with existing grid technologies. NEWT presents computational and data resources through simple transactions against URIs. In this paper we describe our approach to building web applications for science using a RESTful web service. We present the NEWT web service and describe how it can be used to access HPC resources in a web browser environment using AJAX and JSON. We discuss our REST API for NEWT, and address specific challenges in integrating a heterogeneous collection of backend resources under a single web service. We provide examples of client side applications that leverage NEWT to access resources directly in the web browser. The goal of this effort is to create a model whereby HPC becomes easily accessible through the web, allowing users to interact with their scientific computing, data and applications entirely through such web interfaces.