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Titlebook: High Performance Computing; 38th International C Abhinav Bhatele,Jeff Hammond,Carola Kruse Conference proceedings 2023 The Editor(s) (if ap

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樓主: HBA1C
41#
發(fā)表于 2025-3-28 15:56:28 | 只看該作者
CPU Architecture Modelling and Co-designres) as well as HPC applications. The co-design process is frequently based on models. This paper discusses an approach to CPU architecture modelling and its relation to modelling theory. The approach is implemented using the gem5 simulator for Arm-based CPU architectures and applied for the purpose
42#
發(fā)表于 2025-3-28 22:43:48 | 只看該作者
43#
發(fā)表于 2025-3-29 00:56:09 | 只看該作者
44#
發(fā)表于 2025-3-29 06:39:43 | 只看該作者
Efficient GPU Offloading with?OpenMP for?a?Hyperbolic Finite Volume Solver on?Dynamically Adaptive Mptive block-structured Cartesian meshes, which keeps all CPU threads busy and allows all of them to offload sets of patches to the GPU. Our studies show that multithreaded, concurrent, non-deterministic access to the GPU leads to performance breakdowns, since the GPU memory bookkeeping as offered th
45#
發(fā)表于 2025-3-29 10:34:15 | 只看該作者
Shallow Water DG Simulations on?FPGAs: Design and?Comparison of?a?Novel Code Generation Pipelinehigh-level synthesis promise productivity improvements for this technology. However, up to now, FPGA designs for complex simulation workloads, like shallow water simulations based on discontinuous Galerkin discretizations, rely to a large degree on manual application-specific optimizations. In this
46#
發(fā)表于 2025-3-29 14:18:49 | 只看該作者
Massively Parallel Genetic Optimization Through Asynchronous Propagation of?Populationsnt use of HPC resources, . omits the synchronization after each generation as done in conventional genetic algorithms. Instead, it steers the search with the complete population present at time of breeding new individuals. We provide an MPI-based implementation of our algorithm, which features varia
47#
發(fā)表于 2025-3-29 17:48:39 | 只看該作者
48#
發(fā)表于 2025-3-29 20:03:34 | 只看該作者
GPU-Based Low-Precision Detection Approach for Massive MIMO Systems data and the number of connected devices in 5G and beyond. However, M-MIMO systems increase the complexity of recovering the transmitted data (detection phase). To address this challenge, we leverage low-precision arithmetic in recent NVIDIA GPUs to improve the latency/scalability/accuracy of M-MIM
49#
發(fā)表于 2025-3-30 03:03:52 | 只看該作者
50#
發(fā)表于 2025-3-30 04:59:48 | 只看該作者
Ready for?the?Frontier: Preparing Applications for?the?World’s First Exascale Systemers in June 2022 as the very first computer to produce exascale performance. Making sure scientific applications are optimized on this architecture is the critical link necessary to translate the newly available computational power into scientific insight and solutions. To that goal, the OLCF develo
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