Ownership passing

Author:

Friedley Andrew1,Hoefler Torsten2,Bronevetsky Greg3,Lumsdaine Andrew1,Ma Ching-Chen4

Affiliation:

1. Indiana University, Bloomington, IN, USA

2. ETH Zurich, Zurich, Switzerland

3. Lawrence Livermore National Laboratory, Livermore, CA, USA

4. Rose-Hulman Institute of Technology, Terre Haute, IN, USA

Abstract

The number of cores in multi- and many-core high-performance processors is steadily increasing. MPI, the de-facto standard for programming high-performance computing systems offers a distributed memory programming model. MPI's semantics force a copy from one process' send buffer to another process' receive buffer. This makes it difficult to achieve the same performance on modern hardware than shared memory programs which are arguably harder to maintain and debug. We propose generalizing MPI's communication model to include ownership passing, which make it possible to fully leverage the shared memory hardware of multi- and many-core CPUs to stream communicated data concurrently with the receiver's computations on it. The benefits and simplicity of message passing are retained by extending MPI with calls to send (pass) ownership of memory regions, instead of their contents, between processes. Ownership passing is achieved with a hybrid MPI implementation that runs MPI processes as threads and is mostly transparent to the user. We propose an API and a static analysis technique to transform legacy MPI codes automatically and transparently to the programmer, demonstrating that this scheme is easy to use in practice. Using the ownership passing technique, we see up to 51% communication speedups over a standard message passing implementation on state-of-the art multicore systems. Our analysis and interface will lay the groundwork for future development of MPI-aware optimizing compilers and multi-core specific optimizations, which will be key for success in current and next-generation computing platforms.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Graphics and Computer-Aided Design,Software

Cited by 18 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Optimizing MPI Collectives on Shared Memory Multi-Cores;Proceedings of the International Conference for High Performance Computing, Networking, Storage and Analysis;2023-11-11

2. Accelerating Messages by Avoiding Copies in an Asynchronous Task-based Programming Model;2021 IEEE/ACM 6th International Workshop on Extreme Scale Programming Models and Middleware (ESPM2);2021-11

3. FALCON-X: Zero-copy MPI derived datatype processing on modern CPU and GPU architectures;Journal of Parallel and Distributed Computing;2020-10

4. A Disaggregated Packet Processing Architecture for Network Function Virtualization;IEEE Journal on Selected Areas in Communications;2020-06

5. MPI Collectives for Multi-core Clusters;Proceedings of the 48th International Conference on Parallel Processing: Workshops;2019-08-05

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