René Widera

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We present a particle-in-cell simulation of the relativistic Kelvin-Helmholtz Instability (KHI) that for the first time delivers angularly resolved radiation spectra of the particle dynamics during the formation of the KHI. This enables studying the formation of the KHI with unprecedented spatial, angular and spectral resolution. Our results are of great(More)
Porting applications to new hardware or programming models is a tedious and error prone process. Every help that eases these burdens is saving developer time that can then be invested into the advancement of the application itself instead of preserving the status-quo on a new platform. The Alpaka library defines and implements an abstract hierarchical(More)
We present a general framework for GPU-based low-latency data transfer schemes that can be used for a variety of particle-mesh algorithms [8]. This framework allows to hide the latency of the data transfer between GPU-accelerated computing nodes by interleaving it with the kernel execution on the GPU. We discuss as an example the fully relativistic(More)
With the appearance of the heterogeneous platform OpenPower, many-core accelerator devices have been coupled with Power host processors for the first time. Towards utilizing their full potential, it is worth investigating performance portable algorithms that allow to choose the best-fitting hardware for each domain-specific compute task. Suiting even the(More)
The computation power of supercomputers grows faster than the bandwidth of their storage and network. Especially applications using hardware accelerators like Nvidia GPUs cannot save enough data to be analyzed in a later step. There is a high risk of loosing important scientific information. We introduce the in situ template library ISAAC which enables(More)
More and more computationally intensive scientific applications make use of hardware accelerators like general purpose graphics processing units (GPGPUs). Compared to software development for typical multi-core processors their programming is fairly complex and needs hardware specific optimizations to utilize the full computing power. To achieve high(More)
We present an analysis on optimizing performance of a single C++11 source code using the Alpaka hardware abstraction library. For this we use the general matrix multiplication (GEMM) algorithm in order to show that compilers can optimize Alpaka code effectively when tuning key parameters of the algorithm. We do not intend to rival existing, highly optimized(More)
We implement and benchmark parallel I/O methods for the fully-manycore driven particle-in-cell code PIConGPU. Identifying throughput and overall I/O size as a major challenge for applications on today’s and future HPC systems, we present a scaling law characterizing performance bottlenecks in state-of-the-art approaches for data reduction. Consequently, we(More)
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