TY - JOUR
T1 - A workflow runtime environment for manycore parallel architectures
AU - Janetschek, M.
AU - Prodan, R.
AU - Benedict, S.
N1 - Publisher Copyright:
© 2017
PY - 2017/10
Y1 - 2017/10
N2 - We introduce a new Manycore Workflow Runtime Environment (MWRE) to efficiently enact traditional scientific workflows on modern manycore computing architectures. MWRE is compiler-based and translates workflows specified in the XML-based Interoperable Workflow Intermediate Representation (IWIR) into an equivalent C++-based program. This program efficiently enacts the workflow as a stand-alone executable by means of a new callback mechanism that resolves dependencies, transfers data, and handles composite activities. Furthermore, a core feature of MWRE is explicit support for full-ahead scheduling and enactment. Experimental results on a number of real-world workflows demonstrate that MWRE clearly outperforms existing Java-based workflow engines designed for distributed (Grid or Cloud) computing infrastructures in terms of enactment time, is generally better than an existing script-based engine for manycore architectures (Swift), and sometimes gets even close to an artificial baseline implementation of the workflows in the standard OpenMP language for shared memory systems. Experimental results also show that full-ahead scheduling with MWRE using a state-of-the-art heuristic can improve the workflow performance up to 40%.
AB - We introduce a new Manycore Workflow Runtime Environment (MWRE) to efficiently enact traditional scientific workflows on modern manycore computing architectures. MWRE is compiler-based and translates workflows specified in the XML-based Interoperable Workflow Intermediate Representation (IWIR) into an equivalent C++-based program. This program efficiently enacts the workflow as a stand-alone executable by means of a new callback mechanism that resolves dependencies, transfers data, and handles composite activities. Furthermore, a core feature of MWRE is explicit support for full-ahead scheduling and enactment. Experimental results on a number of real-world workflows demonstrate that MWRE clearly outperforms existing Java-based workflow engines designed for distributed (Grid or Cloud) computing infrastructures in terms of enactment time, is generally better than an existing script-based engine for manycore architectures (Swift), and sometimes gets even close to an artificial baseline implementation of the workflows in the standard OpenMP language for shared memory systems. Experimental results also show that full-ahead scheduling with MWRE using a state-of-the-art heuristic can improve the workflow performance up to 40%.
KW - Full-ahead scheduling
KW - Manycores
KW - Scientific workflows
KW - Workflow execution plan
UR - http://www.scopus.com/inward/record.url?scp=85014111392&partnerID=8YFLogxK
U2 - 10.1016/j.future.2017.02.029
DO - 10.1016/j.future.2017.02.029
M3 - Article
AN - SCOPUS:85014111392
SN - 0167-739X
VL - 75
SP - 330
EP - 347
JO - Future Generation Computer Systems
JF - Future Generation Computer Systems
ER -