The Landau Collision Integral in the Particle Basis in the PETSc Library

The Landau collision integral is often considered the gold standard in the context of kinetic plasma simulation due to its conservative properties, despite challenges involved in its discretization. The primary challenge when implementing an efficient computation of this operator is conserving physical properties of the continuum equation when the system is discretized. Recent work has achieved continuum discretizations using the method of Finite Elements which maintain conservation of mass, momentum, and energy, but which lacks monotonic entropy production. More recently, a particle discretization has been introduced which conserves mass, momentum, and energy, but maintains the benefit of monotonic entropy production necessary for the metriplecticity of the system. We present here an implementation of the particle basis Landau collision integral in the Portable Extensible Toolkit for Scientific Computing in 2 and 3V for the construction of a full geometry solver with a novel approach to computation of the entropy functional gradients. Verification of the operator is achieved with thermal equilibration and isotropization tests. All examples are available, open source, in the PETSc repository for reproduction

ALCC Allocation Final Report: HPC Colony II

The report describes those activities of the HPC Colony II Project as they relate to their FY2013 ALCC Award

Asynchronous Teams and Tasks in a Message Passing Environment

As the discipline of scientific computing grows, so too does the "skills gap" between the increasingly complex scientific applications and the efficient algorithms required. Increasing demand for computational power on the march towards exascale requires innovative approaches. Closing the skills gap avoids the many pitfalls that lead to poor utilisation of resources and wasted investment. This thesis tackles two challenges: asynchronous algorithms for parallel computing and fault tolerance. First I present a novel asynchronous task invocation methodology for Discontinuous Galerkin codes called enclave tasking. The approach modifies the parallel ordering of tasks that allows for efficient scaling on dynamic meshes up to 756 cores. It ensures high levels of concurrency and intermixes tasks of different computational properties. Critical tasks along domain boundaries are prioritised for an overlap of computation and communication. The second contribution is the teaMPI library, forming teams of MPI processes exchanging consistency data through an asynchronous "heartbeat". In contrast to previous approaches, teaMPI operates fully asynchronously with reduced overhead. It is also capable of detecting individually slow or failing ranks and inconsistent data among replicas. Finally I provide an outlook into how asynchronous teams using enclave tasking can be combined into an advanced team-based diffusive load balancing scheme. Both concepts are integrated into and contribute towards the ExaHyPE project, a next generation code that solves hyperbolic equation systems on dynamically adaptive cartesian grids

Extreme scale parallel NBody algorithm with event driven constraint based execution model

Traditional scientific applications such as Computational Fluid Dynamics, Partial Differential Equations based numerical methods (like Finite Difference Methods, Finite Element Methods) achieve sufficient efficiency on state of the art high performance computing systems and have been widely studied / implemented using conventional programming models. For emerging application domains such as Graph applications scalability and efficiency is significantly constrained by the conventional systems and their supporting programming models. Furthermore technology trends like multicore, manycore, heterogeneous system architectures are introducing new challenges and possibilities. Emerging technologies are requiring a rethinking of approaches to more effectively expose the underlying parallelism to the applications and the end-users. This thesis explores the space of effective parallel execution of ephemeral graphs that are dynamically generated. The standard particle based simulation, solved using the Barnes-Hut algorithm is chosen to exemplify the dynamic workloads. In this thesis the workloads are expressed using sequential execution semantics, a conventional parallel programming model - shared memory semantics and semantics of an innovative execution model designed for efficient scalable performance towards Exascale computing called ParalleX. The main outcomes of this research are parallel processing of dynamic ephemeral workloads, enabling dynamic load balancing during runtime, and using advanced semantics for exposing parallelism in scaling constrained applications

Monitoring, analysis and optimisation of I/O in parallel applications

High performance computing (HPC) is changing the way science is performed in the 21st Century; experiments that once took enormous amounts of time, were dangerous and often produced inaccurate results can now be performed and refined in a fraction of the time in a simulation environment. Current generation supercomputers are running in excess of 1016 floating point operations per second, and the push towards exascale will see this increase by two orders of magnitude. To achieve this level of performance it is thought that applications may have to scale to potentially billions of simultaneous threads, pushing hardware to its limits and severely impacting failure rates. To reduce the cost of these failures, many applications use checkpointing to periodically save their state to persistent storage, such that, in the event of a failure, computation can be restarted without significant data loss. As computational power has grown by approximately 2x every 18 ? 24 months, persistent storage has lagged behind; checkpointing is fast becoming a bottleneck to performance. Several software and hardware solutions have been presented to solve the current I/O problem being experienced in the HPC community and this thesis examines some of these. Specifically, this thesis presents a tool designed for analysing and optimising the I/O behaviour of scientific applications, as well as a tool designed to allow the rapid analysis of one software solution to the problem of parallel I/O, namely the parallel log-structured file system (PLFS). This thesis ends with an analysis of a modern Lustre file system under contention from multiple applications and multiple compute nodes running the same problem through PLFS. The results and analysis presented outline a framework through which application settings and procurement decisions can be made