MPI versus MPI+OpenMP on IBM SP for the NAS benchmarks
Proceedings of the 2000 ACM/IEEE conference on Supercomputing
Composing high-performance memory allocators
Proceedings of the ACM SIGPLAN 2001 conference on Programming language design and implementation
Hoard: a scalable memory allocator for multithreaded applications
ASPLOS IX Proceedings of the ninth international conference on Architectural support for programming languages and operating systems
False Sharing and Spatial Locality in Multiprocessor Caches
IEEE Transactions on Computers
Development of mixed mode MPI / OpenMP applications
Scientific Programming
IWOMP '07 Proceedings of the 3rd international workshop on OpenMP: A Practical Programming Model for the Multi-Core Era
MPC-MPI: An MPI Implementation Reducing the Overall Memory Consumption
Proceedings of the 16th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface
Thread-local storage extension to support thread-based MPI/OpenMP applications
IWOMP'11 Proceedings of the 7th international conference on OpenMP in the Petascale era
Enabling low-overhead hybrid MPI/OpenMP parallelism with MPC
IWOMP'10 Proceedings of the 6th international conference on Beyond Loop Level Parallelism in OpenMP: accelerators, Tasking and more
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Over the last decade, Message Passing Interface (MPI) has become a very successful parallel programming environment for distributed memory architectures such as clusters. However, the architecture of cluster node is currently evolving from small symmetric shared memory multiprocessors towards massively multicore, Non-Uniform Memory Access (NUMA) hardware. Although regular MPI implementations are using numerous optimizations to realize zero copycache-oblivious data transfers within shared-memory nodes, they might prevent applications from achieving most of the hardware's performance simply because the scheduling of heavyweight processes is not flexible enough to dynamically fit the underlying hardware topology. This explains why several research efforts have investigated hybrid approaches mixing message passing between nodes and memory sharing inside nodes, such as MPI+OpenMP solutions [1,2]. However, these approaches require lots of programming efforts in order to adapt/rewrite existing MPI applications.In this paper, we present the MultiProcessor Communications environnement (MPC), which aims at providing programmers with an efficient runtime system for their existing MPI, POSIX Thread or hybrid MPI+Thread applications. The key idea is to use user-level threads instead of processes over multiprocessor cluster nodes to increase scheduling flexibility, to better control memory allocations and optimize scheduling of the communication flows with other nodes. Most existing MPI applications can run over MPC with no modification. We obtained substantial gains (up to 20%) by using MPC instead of a regular MPI runtime on several scientific applications.