Titlebook: High Performance Computing; 37th International C Ana-Lucia Varbanescu,Abhinav Bhatele,Baboulin Marc Conference proceedings 2022 Springer Na

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书目名称High Performance Computing影响因子(影响力)




书目名称High Performance Computing影响因子(影响力)学科排名




书目名称High Performance Computing网络公开度




书目名称High Performance Computing网络公开度学科排名




书目名称High Performance Computing被引频次




书目名称High Performance Computing被引频次学科排名




书目名称High Performance Computing年度引用




书目名称High Performance Computing年度引用学科排名




书目名称High Performance Computing读者反馈




书目名称High Performance Computing读者反馈学科排名

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LLM: Realizing Low-Latency Memory by Exploiting Embedded Silicon Photonics for Irregular Workloadsency without sacrificing bandwidth and energy efficiency. We propose LLM (Low Latency Memory), a codesign of the DRAM microarchitecture, the memory controller and the LLC/DRAM interconnect by leveraging embedded silicon photonics in 2.5D/3D integrated system on chip. LLM relies on Wavelength Divisio

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SU3_Bench on a Programmable Integrated Unified Memory Architecture (PIUMA) and How that Differs fromderived from the . (LQCD) code used in applications such as Hadron Physics and hence should be of interest to the scientific community..SU3_Bench has a regular compute and data access pattern and on most traditional CPU and GPU-based systems, its performance is mainly determined by the achievable me

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“Hey CAI” - ,onversational ,I Enabled User ,nterface for HPC Toolsf modern HPC systems have necessitated advances in the associated HPC tools making them equally complex with various advanced features and complex user interfaces. While these interfaces are extensive and detailed, they require a steep learning curve even for expert users making them harder to use f

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Efficient Application of Hanging-Node Constraints for Matrix-Free High-Order FEM Computations on CPUtively refined meshes, using matrix-free implementations. We concentrate on unstructured hex-dominated meshes and on multi-component elements with nodal Lagrange shape functions in at least one of their components. The application of general constraints is split up into two distinct operators, one s

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Accelerating Simulated Quantum Annealing with GPU and Tensor Coresa path-integral Monte Carlo simulation, which increases the potential to find the global optima faster than traditional annealing algorithms for large-size combinatorial optimization problems while today’s quantum annealing systems are of a limited number of qubits’. As previous studies have acceler

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-,: An Efficient and Portable Implementation of Multi-dimensional Integration for GPUs systematic uncertainties in physical systems and in Bayesian parameter estimation . Multi-dimensional integration is often time-prohibitive on CPUs. Efficient implementation on many-core architectures is challenging as the workload across the integration space cannot be predicted a priori. We propo