Towards Exascale Scientific Metadata Management

Advances in technology and computing hardware are enabling scientists from all areas of science to produce massive amounts of data using large-scale simulations or observational facilities. In this era of data deluge, effective coordination between the data production and the analysis phases hinges on the availability of metadata that describe the scientific datasets. Existing workflow engines have been capturing a limited form of metadata to provide provenance information about the identity and lineage of the data. However, much of the data produced by simulations, experiments, and analyses still need to be annotated manually in an ad hoc manner by domain scientists. Systematic and transparent acquisition of rich metadata becomes a crucial prerequisite to sustain and accelerate the pace of scientific innovation. Yet, ubiquitous and domain-agnostic metadata management infrastructure that can meet the demands of extreme-scale science is notable by its absence. To address this gap in scientific data management research and practice, we present our vision for an integrated approach that (1) automatically captures and manipulates information-rich metadata while the data is being produced or analyzed and (2) stores metadata within each dataset to permeate metadata-oblivious processes and to query metadata through established and standardized data access interfaces. We motivate the need for the proposed integrated approach using applications from plasma physics, climate modeling and neuroscience, and then discuss research challenges and possible solutions

Performance Characterization of Multi-threaded Graph Processing Applications on Intel Many-Integrated-Core Architecture

Intel Xeon Phi many-integrated-core (MIC) architectures usher in a new era of terascale integration. Among emerging killer applications, parallel graph processing has been a critical technique to analyze connected data. In this paper, we empirically evaluate various computing platforms including an Intel Xeon E5 CPU, a Nvidia Geforce GTX1070 GPU and an Xeon Phi 7210 processor codenamed Knights Landing (KNL) in the domain of parallel graph processing. We show that the KNL gains encouraging performance when processing graphs, so that it can become a promising solution to accelerating multi-threaded graph applications. We further characterize the impact of KNL architectural enhancements on the performance of a state-of-the art graph framework.We have four key observations: 1 Different graph applications require distinctive numbers of threads to reach the peak performance. For the same application, various datasets need even different numbers of threads to achieve the best performance. 2 Only a few graph applications benefit from the high bandwidth MCDRAM, while others favor the low latency DDR4 DRAM. 3 Vector processing units executing AVX512 SIMD instructions on KNLs are underutilized when running the state-of-the-art graph framework. 4 The sub-NUMA cache clustering mode offering the lowest local memory access latency hurts the performance of graph benchmarks that are lack of NUMA awareness. At last, We suggest future works including system auto-tuning tools and graph framework optimizations to fully exploit the potential of KNL for parallel graph processing.Comment: published as L. Jiang, L. Chen and J. Qiu, "Performance Characterization of Multi-threaded Graph Processing Applications on Many-Integrated-Core Architecture," 2018 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), Belfast, United Kingdom, 2018, pp. 199-20

IPCC++: A concurrentC++ for Centralized and Distributed Memory Models.

InterProcess Communication with C++, (IPCC++), is a concurrent object-oriented programming language that supports concurrency for centralized and distributed memory models while maintaining the high level of abstraction associated with object-oriented languages. The IPCC++ language model is a natural extension of the C++ programming language which introduces and supports the following features of concurrency: process concept, mechanism for process instantiation, static and dynamic process declaration, inter-object concurrency, monitor structure, condition variable, socket structure, typed message passing interprocess communication, synchronous and asynchronous communication, client/server paradigm, and run-time communication error detection. Features of concurrency are introduced as complete objects using the primitives of object-oriented programming languages as the vehicle for introduction. The underlying implementation of the components utilizes Parallel Virtual Machine (PVM), a software system that provides an abstraction of the UNIX operating system. A description of the object-oriented and concurrency paradigms are presented. The IPCC++ language model, which represents both paradigms, is defined and an overview of the language and the features it supports is provided. The environment of execution of the IPCC++ language model is described, along with the components of the model used to establish the IPCC++ environment. IPCC++ supports both the centralized and distributed memory models. Each memory model is defined along with the IPCC++ components necessary to support interprocess communication for its corresponding memory model. The centralized memory model uses the monitor structure and the condition variable of concurrency to facilitate centralized interprocess communication. In addition, the distributed memory model uses the socket structure along with a message passing protocol to support distributed interprocess communication. The producer consumer concurrency problem is presented with the corresponding IPCC++ solution designed for a centralized memory model. The dining philosopher concurrency problem is presented with the corresponding IPCC++ solution designed for a distributed memory model. The language design and concurrency features of IPCC++ are discussed and compared with current research efforts that introduce concurrency to C++ supporting centralized and distributed memory models. A description of the IPCC++ implementation model, preprocessing design, and research contributions of the IPCC++ language is provided

On-the-fly memory compression for multibody algorithms.

Memory and bandwidth demands challenge developers of particle-based codes that have to scale on new architectures, as the growth of concurrency outperforms improvements in memory access facilities, as the memory per core tends to stagnate, and as communication networks cannot increase bandwidth arbitrary. We propose to analyse each particle of such a code to find out whether a hierarchical data representation storing data with reduced precision caps the memory demands without exceeding given error bounds. For admissible candidates, we perform this compression and thus reduce the pressure on the memory subsystem, lower the total memory footprint and reduce the data to be exchanged via MPI. Notably, our analysis and transformation changes the data compression dynamically, i.e. the choice of data format follows the solution characteristics, and it does not require us to alter the core simulation code

Frontiers in Pigment Cell and Melanoma Research

We identify emerging frontiers in clinical and basic research of melanocyte biology and its associated biomedical disciplines. We describe challenges and opportunities in clinical and basic research of normal and diseased melanocytes that impact current approaches to research in melanoma and the dermatological sciences. We focus on four themes: (1) clinical melanoma research, (2) basic melanoma research, (3) clinical dermatology, and (4) basic pigment cell research, with the goal of outlining current highlights, challenges, and frontiers associated with pigmentation and melanocyte biology. Significantly, this document encapsulates important advances in melanocyte and melanoma research including emerging frontiers in melanoma immunotherapy, medical and surgical oncology, dermatology, vitiligo, albinism, genomics and systems biology, epidemiology, pigment biophysics and chemistry, and evolution

PICES Press, Vol. 20, No. 1, Winter 2012

•2011 PICES Science: A Note from the Science Board Chairman (pp. 1-6) •2011 PICES Awards (pp. 7-9) •Beyond the Terrible Disaster of the Great East Japan Earthquake (pp. 10-12) •A New Era of PICES-ICES Scientific Cooperation (p. 13) •New PICES Jellyfish Working Group Formed (pp. 14-15) •PICES Working Group on North Pacific Climate Variability (pp. 16-18) •Final U.S. GLOBEC Symposium and Celebration (pp. 19-25) •2011 PICES Rapid Assessment Survey (pp. 26-29) •Introduction to Rapid Assessment Survey Methodologies for Detecting Non-indigenous Marine Species (pp. 30-31) •The 7th International Conference on Marine Bioinvasions (pp. 32-33) •NOWPAP/PICES/WESTPAC Training Course on Remote Sensing Data Analysis (pp. 34-36) •PICES-2011 Workshop on “Trends in Marine Contaminants and their Effects in a Changing Ocean” (pp. 37-39) •The State of the Western North Pacific in the First Half of 2011 (pp. 40-42) •Yeosu Symposium theme sessions (p. 42) •The Bering Sea: Current Status and Recent Events (pp. 43-44) •News of the Northeast Pacific Ocean (pp. 45-47) •Recent and Upcoming PICES Publications (p. 47) •New leadership for the PICES Fishery Science Committee (p. 48

A parallel expert system for the control of a robotic air vehicle

Expert systems can be used to govern the intelligent control of vehicles, for example the Robotic Air Vehicle (RAV). Due to the nature of the RAV system the associated expert system needs to perform in a demanding real-time environment. The use of a parallel processing capability to support the associated expert system's computational requirement is critical in this application. Thus, algorithms for parallel real-time expert systems must be designed, analyzed, and synthesized. The design process incorporates a consideration of the rule-set/face-set size along with representation issues. These issues are looked at in reference to information movement and various inference mechanisms. Also examined is the process involved with transporting the RAV expert system functions from the TI Explorer, where they are implemented in the Automated Reasoning Tool (ART), to the iPSC Hypercube, where the system is synthesized using Concurrent Common LISP (CCLISP). The transformation process for the ART to CCLISP conversion is described. The performance characteristics of the parallel implementation of these expert systems on the iPSC Hypercube are compared to the TI Explorer implementation

Structure, inter-annual variability, and long-term change in zooplankton communities of the Chukchi Sea

Thesis (Ph.D.) University of Alaska Fairbanks, 2016The Chukchi Sea is a complex transition zone between the Pacific and Arctic Oceans that has been experiencing dramatic change in recent decades due to shifting sea ice cover and increasing temperatures. We examine summer mesozooplankton communities of the Chukchi Sea in Alaskan and Russian waters during summers 2004, 2009, 2010 and 2012 within the scope of the RUSALCA (Russian-American Long Term Census of the Arctic) program. Community structure was highly variable between the study years, but was overall tightly correlated to water mass properties, with bottom temperature being the most significant factor influencing communities. Zooplankton biomass was dominated by the large copepod Calanus glacialis, while abundance was dominated by small shelf species of copepods, such as Pseudocalanus spp. and Oithona similis. The “cold" summers of 2009-2012 had nearly twice the biomass and abundance of zooplankton compared to the oceanographically “warm" summer of 2004. We discuss the implications of the inter-annual variability of planktonic communities within the Chukchi Sea, and the possible effects of longer-term climate change. We then look at distribution and population structure of an ecologically important species complex within the zooplankton, Pseudocalanus spp, and evaluate the implications of a warming climate for this group of copepods. While numerically dominating the communities, Pseudocalanus spp. has been historically understudied at the species level due to very subtle morphological differences between the species. Our approach used a combination of microscopic identification as well as a novel species-specific PCR identification method to discriminate between the four species found in the Chukchi Sea. Our results suggest that shifting oceanographic patterns and climate warming will have unequal impact on this group of organisms, arising from species-specific life histories and tolerance to environmental conditions. These recent observations on zooplankton are then placed into a historical context through comparison to data collected throughout the past half-century (1946-2012). Despite significant challenges associated with the highly variable spatial coverage and methodology of the available datasets, significant trends were detected. In addition to high levels of inter-annual variability, we demonstrate significant increases in zooplankton biomass and abundance in recent years compared to historical studies, as well as shifting distribution ranges for several key species. This signal was most pronounced within the copepods, particularly Calanus glacialis, which appears to be indirectly benefiting from warming of the region. While summer zooplankton communities of the Chukchi Sea have been primarily Bering-Pacific in character for as long as our records exist, continuing warming and ice loss are increasing the influence of Bering-Pacific fauna within the Chukchi region