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The collective operations are considered critical for improving the performance of exascale-ready and high-performance computing applications. On this paper we focus on the Message-Passing Interface (MPI) Allgather many to many collective,…
The large variety of production implementations of the message passing interface (MPI) each provide unique and varying underlying algorithms. Each emerging supercomputer supports one or a small number of system MPI installations, tuned for…
MPI implementations commonly rely on explicit memory-copy operations, incurring overhead from redundant data movement and buffer management. This overhead notably impacts HPC workloads involving intensive inter-processor communication. In…
The Message Passing Interface (MPI) is the prevalent programming model used on today's supercomputers. Therefore, MPI library developers are looking for the best possible performance (shortest run-time) of individual MPI functions across…
Massive multiple-input multiple-output (mMIMO) antenna systems and inter-band carrier aggregation (CA)-enabled multi-band communication are two key technologies to achieve very high data rates in beyond fifth generation (B5G) wireless…
The reduce-scatter collective operation in which $p$ processors in a network of processors collectively reduce $p$ input vectors into a result vector that is partitioned over the processors is important both in its own right and as building…
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…
The efficient implementation of collective communiction operations has received much attention. Initial efforts produced "optimal" trees based on network communication models that assumed equal point-to-point latencies between any two…
The \texttt{MPI\_Allreduce} collective operation is a core kernel of many parallel codebases, particularly for reductions over a single value per process. The commonly used allreduce recursive-doubling algorithm obtains the lower bound…
Massive multiple-input multiple-output (mMIMO) regime reaps the benefits of spatial diversity and multiplexing gains, subject to precise channel state information (CSI) acquisition. In the current communication architecture, the downlink…
Collective communications, namely the patterns allgatherv, reduce_scatter, and allreduce in message-passing systems are optimised based on measurements at the installation time of the library. The algorithms used are set up in an…
With the ever-increasing computing power of supercomputers and the growing scale of scientific applications, the efficiency of MPI collective communications turns out to be a critical bottleneck in large-scale distributed and parallel…
MPI uses the concept of communicators to connect groups of processes. It provides nonblocking collective operations on communicators to overlap communication and computation. Flexible algorithms demand flexible communicators. E.g., a…
Message logging protocols are enablers of local rollback, a more efficient alternative to global rollback, for fault tolerant MPI applications. Until now, message logging MPI implementations have incurred the overheads of a redesign and…
A practical and scalable multicast beamformer design in multi-input multi-output~(MIMO) coded caching~(CC) systems is introduced in this paper. The proposed approach allows multicast transmission to multiple groups with partially…
Many parallel applications rely on iterative stencil operations, whose performance are dominated by communication costs at large scales. Several MPI optimizations, such as persistent and partitioned communication, reduce overheads and…
Message Passing Interface (MPI) is a foundational programming model for high-performance computing. MPI libraries traditionally employ network interconnects (e.g., Ethernet and InfiniBand) and network protocols (e.g., TCP and RoCE) with…
Integrating coded caching (CC) into multi-input multi-output (MIMO) setups significantly enhances the achievable degrees of freedom (DoF). We consider a cache-aided MIMO configuration with a CC gain $t$, where a server with $L$ Tx-antennas…
In this work, a new energy-efficiency performance metric is proposed for MIMO (multiple input multiple output) point-to-point systems. In contrast with related works on energy-efficiency, this metric translates the effects of using finite…
Collective operations are common features of parallel programming models that are frequently used in High-Performance (HPC) and machine/ deep learning (ML/ DL) applications. In strong scaling scenarios, collective operations can negatively…