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09/13/2023
Short reasons for long vectors in HPC CPUs: a study based on RISC-V
For years, SIMD/vector units have enhanced the capabilities of modern CP...
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09/11/2023
Compressed Real Numbers for AI: a case-study using a RISC-V CPU
As recently demonstrated, Deep Neural Networks (DNN), usually trained us...
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06/01/2023
Software Development Vehicles to enable extended and early co-design: a RISC-V and HPC case of study
Prototyping HPC systems with low-to-mid technology readiness level (TRL)...
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07/27/2020
A Closer Look at Art Mediums: The MAMe Image Classification Dataset
Art is an expression of human creativity, skill and technology. An excep...
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05/13/2020
MPI+OpenMP Tasking Scalability for Multi-Morphology Simulations of the Human Brain
The simulation of the behavior of the human brain is one of the most amb...
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05/12/2020
Understanding Memory Access Patterns Using the BSC Performance Tools
The growing gap between processor and memory speeds results in complex m...
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11/26/2019
Random Forest as a Tumour Genetic Marker Extractor
Finding tumour genetic markers is essential to biomedicine due to their ...
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11/20/2019
MetH: A family of high-resolution and variable-shape image challenges
High-resolution and variable-shape images have not yet been properly add...
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11/08/2019
Feature discriminativity estimation in CNNs for transfer learning
The purpose of feature extraction on convolutional neural networks is to...
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01/10/2019
Integrating Blocking and Non-Blocking MPI Primitives with Task-Based Programming Models
In this paper we present the Task-Aware MPI library (TAMPI) that integra...
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05/09/2018
MPI+X: task-based parallelization and dynamic load balance of finite element assembly
The main computing tasks of a finite element code(FE) for solving partia...
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04/24/2018
A Visual Distance for WordNet
Measuring the distance between concepts is an important field of study o...
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07/24/2017
Full-Network Embedding in a Multimodal Embedding Pipeline
The current state-of-the-art for image annotation and image retrieval ta...
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07/24/2017
Building Graph Representations of Deep Vector Embeddings
Patterns stored within pre-trained deep neural networks compose large an...
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05/22/2017
An Out-of-the-box Full-network Embedding for Convolutional Neural Networks
Transfer learning for feature extraction can be used to exploit deep rep...
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03/03/2017
On the Behavior of Convolutional Nets for Feature Extraction
Deep neural networks are representation learning techniques. During trai...
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11/02/2016