BOLT: Optimizing OpenMP Parallel Regions with User-Level Threads

Iwasaki, Shinsuke; Amer, Amer; Taura, Kenjiro; Seo, Sangmin; Balaji, Pavan

doi:10.1109/pact.2019.00011

Cited by 17 publications

(14 citation statements)

References 32 publications

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“…Thread scheduling mechanism tailored to the OpenMP specification plays a key role in efficient and effective exploitation of nested parallelism in BOLT. As a result, BOLT outperforms existing OS-level thread-based and ULT-based OpenMP runtime systems [3]. This showcases the importance of exposing low-level threading functionalities including customizable thread schedulers and thread pool operations.…”

Section: Recent Progressmentioning

confidence: 75%

“…Secondly, we developed the work-queue data transfer model for multithreaded MPI communication [31]. We have included support for interaction of MPICH with user-level thread (ULT) libraries [32], primarily targeting Argobots and the BOLT runtime [3]. Other issues that are being looked at include the investigation and evaluation on interaction between MPI and OpenMP and the study and evaluation of MPI endpoints.…”

Section: Solution Strategymentioning

confidence: 99%

“…The training and outreach activity is a cross-cutting effort which is supported by resources from SOLLVE and ECP Broader Engagement, with contributions by external collaborators, notably Lawrence Berkeley National Laboratory. A number of articles have also been published as part of the SOLLVE effort [76,77,78,79,80,81,82,83,84,85,86,87,88,89].…”

Section: Validation and Verification (Vandv)mentioning

confidence: 99%

“…Recent Progress Our recent development of BOLT mainly focuses on efficient OpenMP thread scheduling and management [3]. BOLT takes substantial advantage of its base implementation of LLVM OpenMP in terms of ABI compatibility and coverage of functionalities, while we found the necessity of further performance optimizations to fully exploit fine-grained OpenMP parallel regions.…”

Section: Wbs 23211 Bolt: Lightning Fast Openmpmentioning

confidence: 99%

“…We note that design and implementation of BOLT are highly regarded in the HPC community. The most significant achievement is the Best Paper Award at PACT '19; our paper on BOLT, titled "BOLT: Optimizing OpenMP Parallel Regions with User-Level Threads" [3] won a Best Paper Award at the 28th international conference on Parallel Architectures and Compilation Techniques (PACT '19), which is considered to be a top tier venue in this field. The latest BOLT 1.0rc2 has been upgraded to be compatible with LLVM OpenMP 9.0, which further improves performance and functionalities especially for GPU offloading.…”

Section: Wbs 23211 Bolt: Lightning Fast Openmpmentioning

confidence: 99%

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ECP Software Technology Capability Assessment Report

Heroux

Computing²,

Carter

et al. 2018

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The Exascale Computing Project (ECP) Software Technology (ST) Focus Area is responsible for developing critical software capabilities that will enable successful execution of ECP applications, and for providing key components of a productive and sustainable Exascale computing ecosystem that will position the US Department of Energy (DOE) and the broader high performance (HPC) community with a firm foundation for future extreme-scale computing capabilities. This ECP ST Capability Assessment Report (CAR) provides an overview and assessment of current ECP ST capabilities and activities, giving stakeholders and the broader HPC community information that can be used to assess ECP ST progress and plan their own efforts accordingly. ECP ST leaders commit to updating this document on regular basis (every six to 12 months). Highlights from this version of the report are presented here. What is new in CAR V2.0: CAR V2.0 contains the following updates relative to CAR V1.5. • We introduce the FY20-23 project structure. ECP ST now consists of 6 (up from 5) level-3 (L3) technical areas, introducing the NNSA ST L3 area, which brings into one L3 the ECP open source development efforts at NNSA labs that are of particular importance to the rest of ECP. The number of ECP ST level-4 (L4) subprojects has been reduced from 55 to 33. The strategic aggregation of projects into fewer and larger units enables us to better manage L4 subprojects consistently as a portfolio. See Section 1.2. • We describe new and enhanced project management processes and resources including our iterative planning process, new KPP-3 capability integration process, a product dictionary and dependency management database. These new project features and related dashboards enable more insight and better information to effectively manage efforts across ECP. See Section 2. • The two-page summaries of each ECP L4 projects have been updated to reflect recent progress and next steps. See Section 4. • The Extreme-scale Scientific Software Stack (E4S) is further described. The third release, which is also the first major public release Version 1.0, was November 18, 2019. E4S is the primary integration and delivery vehicle for ECP ST capabilities. See Section 2.1.1. • The ECP ST SDK effort has further refined its groupings. See Section 2.1.2. The Exascale Computing Project Software Technology (ECP ST) focus area represents the key bridge between Exascale systems and the scientists developing applications that will run on those platforms. ECP ST efforts contribute to 70 software products (Section 2.1.3) in six technical areas (Table 1). Since the publishing of CAR V1.5, we have introduced a product dictionary of official product names, which enables more rigorous mapping of ECP ST deliverables to stakeholders (Section 2.1.4). Programming Models & Runtimes: In addition to developing key enhancements to MPI and OpenMP for scalable systems with accelerated node architectures, we are working on performance portability layers (Kokkos and RAJA) and participating in OpenMP and O...

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Section: Recent Progressmentioning

confidence: 75%

Section: Solution Strategymentioning

confidence: 99%