Alex Sim

The Earth System Grid: Supporting the Next Generation of Climate Modeling Research

Understanding the Earths climate system and how it might be changing is a preeminent scientific challenge. Global climate models are used to simulate past, present, and future climates, and experiments are executed continuously on an array of distributed supercomputers. The resulting data archive, spread over several sites, currently contains upwards of 100 TB of simulation data and is growing rapidly. Looking toward mid-decade and beyond, we must anticipate and prepare for distributed climate research data holdings of many petabytes. The Earth System Grid (ESG) is a collaborative interdisciplinary project aimed at addressing the challenge of enabling management, discovery, access, and analysis of these critically important datasets in a distributed and heterogeneous computational environment. The problem is fundamentally a Grid problem. Building upon the Globus toolkit and a variety of other technologies, ESG is developing an environment that addresses authentication, authorization for data access, large-scale data transport and management, services and abstractions for high-performance remote data access, mechanisms for scalable data replication, cataloging with rich semantic and syntactic information, data discovery, distributed monitoring, and Web-based portals for using the system.

Multidimensional indexing and query coordination for tertiary storage management

In many scientific domains, experimental devices or simulation programs generate large volumes of data. The volumes of data may reach hundreds of terabytes and therefore it is impractical to store them on disk systems. Rather they are stored on robotic tape systems that are managed by some mass storage system (MSS). A major bottleneck in analyzing the simulated/collected data is the retrieval of subsets from the tertiary storage system. We describe the architecture and implementation of a Storage Access Coordination System (STACS) designed to optimize the use of a disk cache, and thus minimize the number of files read from tape. We achieve this by using a specialized index to locate the relevant data on tapes, and by coordinating file caching over multiple queries. We focus on a specific application area, a high energy physics data management and analysis environment. STACS was implemented and is being incorporated in an operational system, scheduled to go online at the end of 1999. We also include the results of various tests that demonstrate the benefits and efficiency gained of using the STACS.

A Flexible Reservation Algorithm for Advance Network Provisioning

Many scientific applications need support from a communication infrastructure that provides predictable performance, which requires effective algorithms for bandwidth reservations. Network reservation systems such as ESnets OSCARS, establish guaranteed bandwidth of secure virtual circuits for a certain bandwidth and length of time. However, users currently cannot inquire about bandwidth availability, nor have alternative suggestions when reservation requests fail. In general, the number of reservation options is exponential with the number of nodes n, and current reservation commitments. We present a novel approach for path finding in time-dependent networks taking advantage of user-provided parameters of total volume and time constraints, which produces options for earliest completion and shortest duration. The theoretical complexity is only O(n2r2) in the worst-case, where r is the number of reservations in the desired time interval. We have implemented our algorithm and developed efficient methodologies for incorporation into network reservation frameworks. Performance measurements confirm the theoretical predictions.

High-performance remote access to climate simulation data: a challenge problem for data grid technologies

In numerous scientific disciplines, terabyte and soon petabyte-scale data collections are emerging as critical community resources. A new class of Data Grid infrastructure is required to support management, transport, distributed access to, and analysis of these datasets by potentially thousands of users. Researchers who face this challenge include the Climate Modeling community, which performs long-duration computations accompanied by frequent output of very large files that must be further analyzed. We describe the Earth System Grid prototype, which brings together advanced analysis, replica management, data transfer, request management, and other technologies to support high-performance, interactive analysis of replicated data. We present performance results that demonstrate our ability to manage the location and movement of large datasets from the user’s desktop. We report on experiments conducted over SciNET at SC’2000, where we achieved peak performance of 1.55Gb/s and sustained performance of 512.9Mb/s for data transfers between Texas and California.

An ontology for scientific information in a Grid environment: the earth system Grid

In the emerging world of Grid Computing, shared computational, data, other distributed resources are becoming available to enable scientific advancement through collaborative research and collaboratories. This paper describes the increasing role of ontologies in the context of Grid Computing for obtaining, comparing and analyzing data. We present ontology entities and a declarative model that provide the outline for an ontology of scientific information. Relationships between concepts are also given. The implementation of some concepts described in this ontology is discussed within the context of the Earth System Grid II (ESG)[1].

DataMover: robust terabyte-scale multi-file replication over wide-area networks

Typically, large scientific datasets (order of terabytes) are generated at large computational centers, and stored on mass storage systems. However, large subsets of the data need to be moved to facilities available to application scientists for analysis. File replication of thousands of files is a tedious, error prone, but extremely important task in scientific applications. The automation of the file replication task requires automatic space acquisition and reuse, and monitoring the progress of staging thousands of files from the source mass storage system, transferring them over the network, archiving them at the target mass storage system or disk systems, and recovering from transient system failures. We have developed a robust replication system, called DataMover, which is now in regular use in High-Energy-Physics and Climate modeling experiments. Only a single command is necessary to request multi-file replication or the replication of an entire directory. A Web-based tool was developed to dynamically monitor the progress of the multi-file replication process.

Storage Resource Manager Version 2.2: design, implementation, and testing experience

Storage Services are crucial components of the Worldwide LHC Computing Grid Infrastructure spanning more than 200 sites and serving computing and storage resources to the High Energy Physics LHC communities. Up to tens of Petabytes of data are collected every year by the four LHC experiments at CERN. To process these large data volumes it is important to establish a protocol and a very efficient interface to the various storage solutions adopted by the WLCG sites. In this work we report on the experience acquired during the definition of the Storage Resource Manager v2.2 protocol. In particular, we focus on the study performed to enhance the interface and make it suitable for use by the WLCG communities. At the moment 5 different storage solutions implement the SRM v2.2 interface: BeStMan (LBNL), CASTOR (CERN and RAL), dCache (DESY and FNAL), DPM (CERN), and StoRM (INFN and ICTP). After a detailed inside review of the protocol, various test suites have been written identifying the most effective set of tests: the S2 test suite from CERN and the SRM- Tester test suite from LBNL. Such test suites have helped verifying the consistency and coherence of the proposed protocol and validating existing implementations. We conclude our work describing the results achieved.

Lessons learned from moving earth system grid data sets over a 20 Gbps wide-area network

In preparation for the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report, the climate community will run the Coupled Model Intercomparison Project phase 5 (CMIP-5) experiments, which are designed to answer crucial questions about future regional climate change and the results of carbon feedback for different mitigation scenarios. The CMIP-5 experiments will generate petabytes of data that must be replicated seamlessly, reliably, and quickly to hundreds of research teams around the globe. As an end-to-end test of the technologies that will be used to perform this task, a multi-disciplinary team of researchers moved a small portion (10 TB) of the multimodel Coupled Model Intercomparison Project, Phase 3 data set used in the IPCC Fourth Assessment Report from three sources---the Argonne Leadership Computing Facility (ALCF), Lawrence Livermore National Laboratory (LLNL) and National Energy Research Scientific Computing Center (NERSC)---to the 2009 Supercomputing conference (SC09) show floor in Portland, Oregon, over circuits provided by DOEs ESnet. The team achieved a sustained data rate of 15 Gb/s on a 20 Gb/s network. More important, this effort provided critical feedback on how to deploy, tune, and monitor the middleware that will be used to replicate the upcoming petascale climate datasets. We report on obstacles overcome and the key lessons learned from this successful bandwidth challenge effort.

Storage Resource Managers: Recent International Experience on Requirements and Multiple Co-Operating Implementations

Storage management is one of the most important enabling technologies for large-scale scientific investigations. Having to deal with multiple heterogeneous storage and file systems is one of the major bottlenecks in managing, replicating, and accessing files in distributed environments. Storage resource managers (SRMs), named after their Web services control protocol, provide the technology needed to manage the rapidly growing distributed data volumes, as a result of faster and larger computational facilities. SRMs are grid storage services providing interfaces to storage resources, as well as advanced functionality such as dynamic space allocation and file management on shared storage systems. They call on transport services to bring files into their space transparently and provide effective sharing of files. SRMs are based on a common specification that emerged over time and evolved into an international collaboration. This approach of an open specification that can be used by various institutions to adapt to their own storage systems has proven to be a remarkable success - the challenge has been to provide a consistent homogeneous interface to the grid, while allowing sites to have diverse infrastructures. In particular, supporting optional features while preserving interoperability is one of the main challenges we describe in this paper. We also describe using SRM in a large international high energy physics collaboration, called WLCG, to prepare to handle the large volume of data expected when the Large Hadron Collider (LHC) goes online at CERN. This intense collaboration led to refinements and additional functionality in the SRM specification, and the development of multiple interoperating implementations of SRM for various complex multi- component storage systems.

Experiences with 100Gbps network applications

100Gbps networking has finally arrived, and many research and educational institutions have begun to deploy 100Gbps routers and services. ESnet and Internet2 worked together to make 100Gbps networks available to researchers at the Supercomputing 2011 conference in Seattle Washington. In this paper, we describe two of the first applications to take advantage of this network. We demonstrate a visualization application that enables remotely located scientists to gain insights from large datasets. We also demonstrate climate data movement and analysis over the 100Gbps network. We describe a number of application design issues and host tuning strategies necessary for enabling applications to scale to 100Gbps rates.