41 citations · 166 across the 13 of their papers we have counts for
13 papers
DMRlib: Easy-coding and Efficient Resource Management for Job Malleability
Sergio Iserte, Rafael Mayo, Enrique S. Quintana-Ortí +1
Process malleability has proved to have a highly positive impact on the resource utilization and global productivity in data centers compared with the conventional static resource…
The Fused Kernel Library: A C++ API to Develop Highly-Efficient GPU Libraries
Oscar Amoros, Albert Andaluz, Johnny Nunez +1
Existing GPU libraries often struggle to fully exploit the parallel resources and on-chip memory (SRAM) of GPUs when chaining multiple GPU functions as individual kernels. While Ke…
ACC Saturator: Automatic Kernel Optimization for Directive-Based GPU Code
Kazuaki Matsumura, Simon Garcia De Gonzalo, Antonio J. Peña
Automatic code optimization is a complex process that typically involves the application of multiple discrete algorithms that modify the program structure irreversibly. However, th…
A Symbolic Emulator for Shuffle Synthesis on the NVIDIA PTX Code
Kazuaki Matsumura, Simon Garcia De Gonzalo, Antonio J. Peña
Various kinds of applications take advantage of GPUs through automation tools that attempt to automatically exploit the available performance of the GPU's parallel architecture. Di…
JACC: An OpenACC Runtime Framework with Kernel-Level and Multi-GPU Parallelization
Kazuaki Matsumura, Simon Garcia De Gonzalo, Antonio J. Peña
The rapid development in computing technology has paved the way for directive-based programming models towards a principal role in maintaining software portability of performance-c…
Particle-In-Cell Simulation using Asynchronous Tasking
Nicolas Guidotti, Pedro Ceyrat, João Barreto +5
Recently, task-based programming models have emerged as a prominent alternative among shared-memory parallel programming paradigms. Inherently asynchronous, these models provide na…
Enabling Homomorphically Encrypted Inference for Large DNN Models
Guillermo Lloret-Talavera, Marc Jorda, Harald Servat +5
The proliferation of machine learning services in the last few years has raised data privacy concerns. Homomorphic encryption (HE) enables inference using encrypted data but it inc…
cuConv: A CUDA Implementation of Convolution for CNN Inference
Marc Jordà, Pedro Valero-Lara, Antonio J. Peña
Convolutions are the core operation of deep learning applications based on Convolutional Neural Networks (CNNs). Current GPU architectures are highly efficient for training and dep…
DMR API: Improving cluster productivity by turning applications into malleable
Sergio Iserte, Rafael Mayo, Enrique S. Quintana-Orti +2
Adaptive workloads can change on--the--fly the configuration of their jobs, in terms of number of processes. In order to carry out these job reconfigurations, we have designed a me…
Understanding Memory Access Patterns Using the BSC Performance Tools
Harald Servat, Jesús Labarta, Hans-Christian Hoppe +2
The growing gap between processor and memory speeds results in complex memory hierarchies as processors evolve to mitigate such divergence by taking advantage of the locality of re…
MPI+OpenMP Tasking Scalability for Multi-Morphology Simulations of the Human Brain
Pedro Valero-Lara, Raül Sirvent, Antonio J. Peña +1
The simulation of the behavior of the human brain is one of the most ambitious challenges today with a non-end of important applications. We can find many different initiatives in…
Integrating Blocking and Non-Blocking MPI Primitives with Task-Based Programming Models
Kevin Sala, Xavier Teruel, Josep M. Perez +3
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 leve…
Exploring the Vision Processing Unit as Co-processor for Inference
Sergio Rivas-Gomez, Antonio J. Peña, David Moloney +2
The success of the exascale supercomputer is largely debated to remain dependent on novel breakthroughs in technology that effectively reduce the power consumption and thermal diss…