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Past Projects

Projects from current and former CLaSS members that have been replaced by follow-on work or are no longer actively being pursued.

Berkeley Lab Checkpoint/Restart (BLCR) for LINUX

This work focuses on checkpointing parallel applications that communicate through MPI, and on compatibility with the software suite produced by the SciDAC Scalable Systems Software ISIC. Read More »

CORVETTE: Correctness Verification and Testing of Parallel Programs

Research Topics The goal of this project is to provide tools to assess the correctness of parallel programs written using hybrid parallelism. There is a dire lack of both theoretical and engineering know-how in the area of finding bugs in hybrid or large scale parallel programs, which our research aims to change. As intranode programming is likely to be the most disrupted by the transition to Exascale, we will emphasize support for a large spectrum of programming and execution models such as… Read More »

DEGAS: Dynamic Exascale Global Address Space Programming Environments

Dynamic Exascale Global Address Space Programming Environments The Dynamic, Exascale Global Address Space programming environment (DEGAS) project will develop the next generation of programming models, runtime systems and tools to meet the challenges of Exascale systems.  We will develop a new set of programming concepts based on a hierarchical model of parallelism and data locality, hierarchical fault containment/recovery for resilience, introspective dynamic resource management, demonstrate… Read More »

FastOS

Overview Chip multiprocessors containing hundreds or even thousands of cores will challenge current operating systems (OS) practices. Many of the fundamental assumptions that underlie current OS technology are based on design assumptions that are no longer valid for a chip multiprocessor (CMP) containing thousands of cores. In the context of handheld devices, the OS must manage quality-of-service and resource contention for a complex multi-programmed environment. In the context of high… Read More »

Intel Parallel Computing Center: Big Data Support on HPC Systems

Personnel: Costin Iancu and Khaled Ibrahim (LBNL), Nicholas Chaimov (U. Oregon)    To extend their mission and to open new science frontiers, operators of large scale supercomputers have a vested interest to deploy existing data analytics frameworks such as Spark or Hadoop.  So far, this deployment has been hampered by the differences in system architecture, which are reflected in the design approach for the analytics stacks. HPC systems are the mirrored image of data centers. In a… Read More »