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Modern powerful accelerators and composable infrastructures put our simulation frameworks to the test. We will show that the acceleration of a simulation framework is absolutely critical for good performance and scaling. Building on our previous work ...

The lattice Boltzmann method is a highly scalable Navier-Stokes solver that has been applied to flow problems in a wide array of domains. However, the method is bandwidth-bound on modern GPU accelerators and has a large memory footprint. In this paper, ...

GPUs pose an attractive opportunity for delivering high-performance applications. However, GPU codes are often limited due to memory contention, resulting in overall performance degradation. Since GPU scheduling is transparent to the user, and GPU ...

In recent history, GPUs became a key driver of compute performance in HPC. With the installation of the Frontier supercomputer, they became the enablers of the Exascale era; further largest-scale installations are in progress (Aurora, El Capitan, ...

In an era of increasing computer system diversity, the portability of software from one system to another plays a central role. Software portability is important for the software developers as many software projects have a lifetime ...

• We discuss the Ginkgo design separating the numerical core from the architecture-specific backends written in the architecture-specific language to allow for ...

Convolutional Neural Networks, and many other machine learning algorithms, use Graphical Processing Units (GPUs) instead of Central Processing Units (CPUs) to improve the training time of very large modeling computations. This work evaluates the ...

The abstraction of a shared memory space over separate CPU and GPU memory domains has eased the burden of portability for many HPC codebases. However, users pay for the ease of use provided by systems-managed memory space with a moderate-to-high ...

Heterogeneous systems are becoming increasingly prevalent. In order to exploit the rich compute resources of such systems, robust programming models are needed for application developers to seamlessly migrate legacy code from today’s systems to ...

The Cray XK7 Titan was the top supercomputer system in the world for a long time and remained critically important throughout its nearly seven year life. It was an interesting machine from a reliability viewpoint as most of its power came from 18,688 ...

The HPGMG benchmark is a non-trivial Multigrid benchmark used to evaluate system performance. We ported this benchmark from CUDA to OpenMP target offload and added the capability to use explicit data management rather than managed memory. Our ...

Efficiently processing sparse matrices is a central and performance-critical part of many scientific simulation codes. Recognizing the adoption of manycore accelerators in HPC, we evaluate in this paper the performance of the currently best ...

• Parallelization with GPU is proposed for fast computation of first passage time.

The numerical integration of stochastic trajectories to estimate the time to pass a threshold is an interesting physical quantity, for instance in Josephson junctions and atomic force microscopy, where the full trajectory is not ...

Segmented sort, as a generalization of classical sort, orders a batch of independent segments in a whole array. Along with the wider adoption of manycore processors for HPC and big data applications, segmented sort plays an increasingly important role ...

Spatial blocking is a critical memory-access optimization to efficiently exploit the computing resources of parallel processors, such as many-core GPUs. By reusing cache-loaded data over multiple spatial iterations, spatial blocking can significantly ...

GMDH, which stands for Group Method Data Handling, is an evolutionary type of neural network. It has received much attention in the supercomputing research community because of its ability to optimize its internal structure for maximum prediction ...

In this paper, we show that the GPU (graphics processing unit) can be used not only for processing graphics, but also for high speed computing. We provide a comparison between the times taken on the CPU and GPU to perform the training and testing of a ...

Convex polyhedra represent granular media well. This geometric representation may be critical in obtaining realistic simulations of many industrial processes using the discrete element method (DEM). However detecting collisions between the polyhedra and ...

To exploit the abundant computational power of the world's fastest supercomputers, an even workload distribution to the typically heterogeneous compute devices is necessary. While relatively accurate performance models exist for conventional CPUs, ...

The amount of business data generated and collected is increasing exponentially every year. There are studies pointing out that using GPU as a general-purpose computing device has limitations. In order to exploit current GPU computing capabilities for ...

The amount of business data generated and collected is increasing exponentially every year. A Graphics Processing Unit (GPU) is not used for only optimization of image filtering and video processing, but is also widely adopted for accelerating big data ...