Titlebook: Euro-Par 2020: Parallel Processing; 26th International C Maciej Malawski,Krzysztof Rzadca Conference proceedings 2020 Springer Nature Switz

可行

Skipping Non-essential Instructions Makes Data-Dependence Profiling Fastersis, which may overestimate the number of dependences because it does not know many pointers values and array indices at compile time, profiling has the advantage of recording data dependences that actually occur at runtime. But it has the disadvantage of significantly slowing down program execution

Odyssey

exceed

Towards a Model to Estimate the Reliability of Large-Scale Hybrid Supercomputerss, and machine learning executions require high performance computing platforms. Such infrastructures have been growing lately with the addition of thousands of newly designed components, calling their resiliency into question. It is crucial to solidify our knowledge on the way supercomputers fail.

記憶

串通

Operation-Aware Power Cappingr’s power consumption needs to be capped to avoid hardware damage. However, power capping often causes a computational performance loss because the underlying processors are clocked down. In this work, we developed an operation-aware management strategy, called ., to mitigate the performance loss. .

Obliterate

A Comparison of the Scalability of OpenMP Implementationsormance at scale. Previous work has shown that overheads do not scale favourably in commonly used OpenMP implementations. Focusing on synchronization overhead, this work analyses the overhead of core OpenMP runtime library components for GNU and LLVM compilers, reflecting on the implementation’s sou