Performance Reproduction and Prediction of Selected Dynamic Loop Scheduling Experiments

Abstract

and modern hardware leads to an entirely different behavior from expected. This work paves the way towards additional simulative and native experimentation using further DLS techniques in the future.

An approach for realistically simulating the performance of scientific applications on high performance computing systems

“…The present work builds upon and extends own prior work [5] [6], which focused on the experimental verification of DLS implementation via reproduction [6] and the experimental verification of application's performance simulation on HPC systems [5], respectively. In the present work, a new method to represent the computational effort in tasks is explored and tested (c.f.…”

“…A number of dynamic loop self-scheduling (DLS) techniques have been proposed between the late 1980s and early 2000s, and efficiently used in scientific applications [18]. Dynamic nonadaptive techniques have previously been verified [6] by reproduction of the original experiments that introduced them [14] using the experimental verification approach illustrated by step 1 in Figure 1. In this work, the range of studied DLS techniques is extended with four adaptive DLS techniques in addition to the nonadaptive ones.…”

“…The experiment was repeated 20 times for each application to ensure that the FLOP count is constant in all repetitions. The FLOP count can be also inferred from the application source code [6] in case of simple dense linear algebra kernels. The resulting FLOP count per task is written to a file that is read by the simulator to account for task execution times.…”

“…Through the first perspective, the performance reported in the original publications, which introduced the most well-known, successful, and currently used DLS techniques from the past, is presently reproduced via simulation to verify the the similarity in performance results between the current DLS techniques implementations and their original implementation [6].…”

SiL: An Approach for Adjusting Applications to Heterogeneous Systems Under Perturbations

“…The DLS techniques can be implemented using centralized or decentralized execution and control approach. The decentralized control approach was found to scale better by eliminating a centralized master, and hence, the master-level contention [18]. The DLS implemented using the decentralized control approach is considered in this work.…”