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This paper investigates session programming and typing of benchmark examples to compare productivity, safety and performance with other communications programming languages. Parallel algorithms are used to examine the above aspects due to…

Message Passing Interfaces (MPI) plays an important role in parallel computing. Many parallel applications are implemented as MPI programs. The existing methods of bug detection for MPI programs have the shortage of providing both input and…

Program correctness is one of the most difficult challenges in parallel programming. Message Passing Interface MPI is widely used in writing parallel applications. Since MPI is not a compiled language, the programmer will be enfaced with…

The Message Passing Interface (MPI) is the de facto standard message-passing infrastructure for developing parallel applications. Two decades after the first version of the library specification, MPI-based applications are nowadays…

HPC systems keep growing in size to meet the ever-increasing demand for performance and computational resources. Apart from increased performance, large scale systems face two challenges that hinder further growth: energy efficiency and…

We discuss the computational bottlenecks in molecular dynamics (MD) and describe the challenges in parallelizing the computation intensive tasks. We present a hybrid algorithm using MPI (Message Passing Interface) with OpenMP threads for…

With the ever-increasing computing power of supercomputers and the growing scale of scientific applications, the efficiency of MPI collective communication turns out to be a critical bottleneck in large-scale distributed and parallel…

MDMP is a new parallel programming approach that aims to provide users with an easy way to add parallelism to programs, optimise the message passing costs of traditional scientific simulation algorithms, and enable existing MPI-based…

In this paper we present the Task-Aware MPI library (TAMPI) that integrates both blocking and non-blocking MPI primitives with task-based programming models. The TAMPI library leverages two new runtime APIs to improve both programmability…

Removing the CPU from the communication fast path is essential to efficient GPU-based ML and HPC application performance. However, existing GPU communication APIs either continue to rely on the CPU for communication or rely on APIs that…

Faults in high-performance systems are expected to be very large in the current exascale computing era. To compensate for a higher failure rate, the standard checkpoint/restart technique would need to create checkpoints at a much higher…

Two-phase I/O is a well-known strategy for implementing collective MPI-IO functions. It redistributes I/O requests among the calling processes into a form that minimizes the file access costs. As modern parallel computers continue to grow…

The Message Passing Interface (MPI) is a fundamental tool for building high-performance computing (HPC) applications, enabling efficient communication across distributed systems. Despite its widespread adoption, MPI's low-level interface…

Message Passing Interface (MPI) has been a well-established technology in the domain of distributed high-performance computing for several decades. However, one of its greatest drawbacks is a rather ancient pure-C interface. It lacks many…

Existing Deep Learning frameworks exclusively use either Parameter Server(PS) approach or MPI parallelism. In this paper, we discuss the drawbacks of such approaches and propose a generic framework supporting both PS and MPI programming…

Clusters of SMP nodes provide support for a wide diversity of parallel programming paradigms. Combining both shared memory and message passing parallelizations within the same application, the hybrid MPI-OpenMP paradigm is an emerging trend…

MPI is the most widely used interface for high-performance computing (HPC) workloads. Its success lies in its embrace of libraries and ability to evolve while maintaining backward compatibility for older codes, enabling them to run on new…

Dynamic scaling aims to elastically change the number of processes during runtime to tune the performance of the distributed applications. This report briefly presents a performance evaluation of MPI process provisioning / de-provisioning…

InfiniBand is widely used for low-latency, high-throughput cluster computing. Saving the state of the InfiniBand network as part of distributed checkpointing has been a long-standing challenge for researchers. Because of a lack of a…

Offload of MPI collectives to network devices, e.g., NICs and switches, is being implemented as an effective mechanism to improve application performance by reducing inter- and intra-node communication and bypassing MPI software layers.…