Approximation Scheme in Space and Time. The naive use of increasingly more processors for a fixed-size N-body problem is prone to saturate as soon as the number of unknowns per core becomes too small. To overcome this intrinsic strong-scaling limit, we introduce temporal parallelism on top of PEPC’s existing hybrid MPI/PThreads spatial decomposition. Here, we use PFASST which is based on a combination of the iterations of the parallel-in-time algorithm parareal with the sweeps of spectral deferred correction (SDC) schemes. By combining these sweeps with multiple space-time discretization levels, PFASST relaxes the theoretical bound on parallel efficiency in parareal. We present results from runs on up to 262,144 cores on the IBM Blue Gene/P...
I will give a brief overview of iterative methods based on Spectral Deferred Corrections and highlig...
MotivationWith growing interest in parallel-in-time methods many different and new solvers for ordin...
I describe here the performances of a parallel treecode with individual particle timesteps. The code...
The efficient use of modern supercomputers has become one of the key challenges in computational sci...
To extend prevailing scaling limits when solving time-dependent partial differential equations, the ...
The challenging problems arising from fast parallel N-body simulations became a driver for high perf...
While many ideas and proofs of concept for parallel-in-time integration methods exists, the number o...
The efficient parallelization of fast multipole-based algorithms for the N-body problem is one of th...
I describe here the performance of a parallel treecode with individual particle timesteps. The code ...
The parallel full approximation scheme in space and time (PFASST) allows to integrate multiple time-...
In this article, we present the Python framework pySDC for solving collocation problems with spectra...
The parallel full approximation scheme in space and time (PFASST) introduced by Emmett and Minion in...
The PFASST algorithm is a time-parallel algorithm for solving ODEs and PDEs. The PFASST project is a...
The "parallel full approximation scheme in space and time" (PFASST) is an iterative, multilevel stra...
Spectral deferred corrections (SDC) are an easy way to construct higher-order time integration schem...
I will give a brief overview of iterative methods based on Spectral Deferred Corrections and highlig...
MotivationWith growing interest in parallel-in-time methods many different and new solvers for ordin...
I describe here the performances of a parallel treecode with individual particle timesteps. The code...
The efficient use of modern supercomputers has become one of the key challenges in computational sci...
To extend prevailing scaling limits when solving time-dependent partial differential equations, the ...
The challenging problems arising from fast parallel N-body simulations became a driver for high perf...
While many ideas and proofs of concept for parallel-in-time integration methods exists, the number o...
The efficient parallelization of fast multipole-based algorithms for the N-body problem is one of th...
I describe here the performance of a parallel treecode with individual particle timesteps. The code ...
The parallel full approximation scheme in space and time (PFASST) allows to integrate multiple time-...
In this article, we present the Python framework pySDC for solving collocation problems with spectra...
The parallel full approximation scheme in space and time (PFASST) introduced by Emmett and Minion in...
The PFASST algorithm is a time-parallel algorithm for solving ODEs and PDEs. The PFASST project is a...
The "parallel full approximation scheme in space and time" (PFASST) is an iterative, multilevel stra...
Spectral deferred corrections (SDC) are an easy way to construct higher-order time integration schem...
I will give a brief overview of iterative methods based on Spectral Deferred Corrections and highlig...
MotivationWith growing interest in parallel-in-time methods many different and new solvers for ordin...
I describe here the performances of a parallel treecode with individual particle timesteps. The code...