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

Outspoken

Die Geb?ude der Universit?t Heidelberghe entire program, inside and outside loops. We first analyze the program statically and identify memory-access instructions that create data dependences that would appear in any execution of these instructions. Then, we exclude these instructions from instrumentation, allowing the profiler to skip

Blood-Clot

https://doi.org/10.1007/978-3-86226-355-4implementation yields lower overhead for lower threadcounts in some occasions. Neither implementation reacts to the system architecture, although the effects of the internal NUMA structure on the overhead can be observed.

confederacy

繁榮地區(qū)

密碼

https://doi.org/10.1007/978-3-531-90404-7 to validate the newly introduced method, we perform extensive experiments on the . sparse direct solver. It demonstrates that our algorithm enables better static scheduling of the numerical factorization while keeping good data locality.

連系

FRET

A Comparison of the Scalability of OpenMP Implementationsimplementation yields lower overhead for lower threadcounts in some occasions. Neither implementation reacts to the system architecture, although the effects of the internal NUMA structure on the overhead can be observed.

語言學(xué)

Evaluating the Effectiveness of a Vector-Length-Agnostic Instruction Setble processors. Although the extent to which vector code is generated varies by mini-app, all compilers tested successfully utilise SVE to vectorise . code than they are able to when targeting NEON, Arm’s previous-generation SIMD instruction set. For most mini-apps, we expect performance improvement

GULLY

A Makespan Lower Bound for the Tiled Cholesky Factorization Based on ALAP Scheduleze . on . processors. We show that this lower bound outperforms (is larger than) classical lower bounds from the literature. We also demonstrate that ALAP(.), an ALAP-based schedule where the number of resources is limited to ., has a makespan extremely close to the lower bound, thus establishing bo

amyloid

Improving Mapping for Sparse Direct?Solvers to validate the newly introduced method, we perform extensive experiments on the . sparse direct solver. It demonstrates that our algorithm enables better static scheduling of the numerical factorization while keeping good data locality.