Related papers: A Data-Parallel Version of Aleph
Running parallel applications requires special and expensive processing resources to obtain the required results within a reasonable time. Before parallelizing serial applications, some analysis is recommended to be carried out to decide…
The Adapteva Epiphany many-core architecture comprises a 2D tiled mesh Network-on-Chip (NoC) of low-power RISC cores with minimal uncore functionality. It offers high computational energy efficiency for both integer and floating point…
Application development for distributed computing "Grids" can benefit from tools that variously hide or enable application-level management of critical aspects of the heterogeneous environment. As part of an investigation of these issues,…
Nowadays, clusters of multicores are becoming the norm and, although, many or-parallel Prolog systems have been developed in the past, to the best of our knowledge, none of them was specially designed to explore the combination of shared…
This paper introduces a parallel and asynchronous Transformer framework designed for efficient and accurate multilingual lip synchronization in real-time video conferencing systems. The proposed architecture integrates translation, speech…
As multicore computing is now standard, it seems irresponsible for constraints researchers to ignore the implications of it. Researchers need to address a number of issues to exploit parallelism, such as: investigating which constraint…
The Message Passing Interface specification (MPI) defines a portable message-passing API used to program parallel computers. MPI programs manifest a number of challenges on what concerns correctness: sent and expected values in…
The Message Passing Interface (MPI) is the most commonly used application programming interface for process communication on current large-scale parallel systems. Due to the scale and complexity of modern parallel architectures, it is…
Processing massive application graphs on distributed memory systems requires to map the graphs onto the system's processing elements (PEs). This task becomes all the more important when PEs have non-uniform communication costs or the input…
The MARS15 Monte Carlo code capabilities to deal with time-consuming deep penetration shielding problems and other computationally tough tasks in accelerator, detector and shielding applications, have been enhanced by a parallel processing…
Alpa automates model-parallel training of large deep learning (DL) models by generating execution plans that unify data, operator, and pipeline parallelism. Existing model-parallel training systems either require users to manually create a…
The present paper is the first of a series of papers reporting on the parallelization of the symbolic manipulation program FORM on different parallel architectures. Part I deals with workstation clusters using dedicated network hardware and…
Many modern, high-performance systems increase the cumulated node-bandwidth by offering more than a single communication network and/or by having multiple connections to the network. Efficient algorithms and implementations for collective…
The current trend of multicore architectures on shared memory systems underscores the need of parallelism. While there are some programming model to express parallelism, thread programming model has become a standard to support these system…
Message Passing Interface (MPI) is widely used to implement parallel programs. Although Windowsbased architectures provide the facilities of parallel execution and multi-threading, little attention has been focused on using MPI on these…
As we have entered Exascale computing, the faults in high-performance systems are expected to increase considerably. To compensate for a higher failure rate, the standard checkpoint/restart technique would need to create checkpoints at a…
Heterogeneous clusters with nodes containing one or more accelerators, such as GPUs, have become common. While MPI provides inter-address space communication, and OpenCL provides a process with access to heterogeneous computational…
Future applications demand more performance, but technology advances have been faltering. A promising approach to further improve computer system performance under energy constraints is to employ hardware accelerators. Already today, mobile…
Large language models (LLMs) are widely used for natural language understanding and text generation. An LLM model relies on a time-consuming step called LLM decoding to generate output tokens. Several prior works focus on improving the…
Parsl is a parallel programming library for Python that aims to make it easy to specify parallelism in programs and to realize that parallelism on arbitrary parallel and distributed computing systems. Parsl relies on developers annotating…