CV Lattes
GoogleMyCitations
Ministério da Educação (Brasil). Universidade Federal do ABC (UFABC). Centro de Matemática, Computação e Cognição (CMCC) (Institutional affiliation for the last research proposal) Birthplace: Brazil
Raphael Y. de Camargo is an Associate Professor at Federal University of ABC (UFABC), at the Center for Mathematics, Computing and Cognition. He holds a PhD in Computer Science from IME / USP, a Masters from IF / USP and a Bachelor of Science in Molecular Sciences from USP. He is currently permanent advisor in the Master's and Doctoral programs in Computer Science and Neuroscience and Cognition, at Federal University of ABC. He has experience and work in: (1) High performance computing (GPGPU, heterogeneous computing and scheduling), (2) Machine Learning (high performance computing, smart cities and neuroscience applications), and (3) Computational neuroscience (computational models of memory and time perception, connectivity analysis and decoding of neural signals). (Source: Lattes Curriculum)
| News published in Agência FAPESP Newsletter about the researcher |
| TITULO |
| Articles published in other media outlets (0 total): |
| More itemsLess items |
| VEICULO: TITULO (DATA) |
| VEICULO: TITULO (DATA) |
Universidade Federal do ABC (UFABC) is one of the new Brazilian Federal universities, created on July 26, 2005. For this reason, the support of development agencies is indeed essential for performing high-level research. In this proposal, we present a project to use the institutional infrastructure parcel of the Center for Mathematics, Computation and Cognition (CMCC). This proposal focus…
With the advent of different classes of accelerators such as GPUs (Graphical Processing Units) and Intel MIC (Many Integrated Cores), heterogeneous clusters composed of different types of accelerators and processors became reality. We consider dedicated and shared clusters, the later composed of shared workstations distributed in several laboratories. The architectural differences between…
Nowadays, the general-purpose computing on graphical processing units (GPGPU) technique is widely accepted as a new paradigm of High Performance Computing for improving the performance of simulations, such as large-scale neuronal simulations. In this work we will develop an algorithm for solving a large sets of linear systems, each representing a single neuron, using GPUs. We will incorpo…
| 3 / 3 | Completed research grants |
| 3 / 1 | Completed scholarships in Brazil |
| 6 / 4 | All research grants and scholarships |
| Associated processes | |
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
| Publications | 2 |
| Citations | 3 |
| Cit./Article | 1.5 |
| Data from Web of Science | |
CARASTAN-SANTOS, DANILO; MARTINS-, JR., DAVID C.; SONG, SIANG W.; ROZANTE, LUIZ C. S.; DE CAMARGO, RAPHAEL Y.. A hybrid CPU-GPU-MIC algorithm for minimal hitting set enumeration. CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, v. 31, n. 18, SI, SEP 25 2019. Web of Science Citations: 1. (15/24485-9, 14/50937-1, 15/01587-0, 13/26644-1)
CARASTAN-SANTOS, DANILO; DE CAMARGO, RAPHAEL Y.; MARTINS, JR., DAVID C.; SONG, SIANG W.; ROZANTE, LUIZ C. S.. Finding exact hitting set solutions for systems biology applications using heterogeneous GPU clusters. FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, v. 67, p. 418-429, FEB 2017. Web of Science Citations: 2. (13/26644-1)
(References retrieved automatically from State of São Paulo Research Institutions)
CAMARGO, Raphael Yokoingawa de. Inferência de conexões sinápticas em redes neurais biologicamente plausíveis. 108 f. Dissertação (Mestrado) - Instituto de Física. Universidade de São Paulo (USP). São Paulo. (00/14010-8)