To be held in conjunction with the 29th International Symposium on
Computer Architecture and High Performance Computing (SBAC-PAD 2017)

Writing parallel applications is an arduous and non-trivial task, but also mandatory if one wants to explore the potential of modern multicore processors. This task becomes even harder as different computation devices, such as General Purpose Graphic Processing Units (GPGPUs) and Field Programmable Gate Arrays (FPGAs), are employed to build heterogeneous systems. This imposes new challenges to the scientific community: the creation of models and alternatives to ease parallelism exploitation by the average programmer, considering the peculiarities of the different computation devices.

Another important aspect to consider, specially in applications that run on big systems and manipulate big datasets, is the tradeoff between moving data to a remote processing element to increase parallelism and computing things locally to reduce communication costs. Fog and in-situ computing intend to tackle this issue by adding computing capabilities to network devices (such as NICs, switches and routers), storage devices or even memory. Those "smart" devices would be able to perform part of the computation that would reduce data transmission over the network and data busses. This makes computing systems even more heterogeneous, intensifying the need of novel programming models.

MPP aims at bringing together researchers interested in presenting contributions to the evolution of existing models or in proposing novel ones, considering the trends on accelerator devices and fog/in-situ computing. MPP 2017 will be held in conjunction with the 29th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD 2017), at Campinas, São Paulo, Brazil.

MPP invites authors to submit unpublished full papers on the subject. Submissions must be in English, 6 pages maximum, following the IEEE formatting guidelines. The 6-page limit includes references. Topics of interest include (but are not limited to):
Data-Flow execution models and languages for parallelism exploitation;
Languages, compilers and parallelism extraction tools
Heterogeneous programming models
Synchronization Mechanisms, such as Transactional Memories
Load-balancing for multithreading
Scheduling and Placement Algorithms for Parallel Programming models
Novel Parallel Programming Techniques
Novel Parallel Architectures
Error Detection/Recovery for Parallel Programming Models
Theoretical Analysis of Parallelism.
Smart storage and in-situ computing
Fog computing


Program co-chairs
Leandro Augusto Justen Marzulo - UERJ, Brazil
Felipe M. G. França - UFRJ, Brazil
Cristiana Bentes - UERJ, Brazil
Vladimir Alves - NGD Systems, USA

Program Committee
Alexandre da Costa Sena - Universidade do Estado do Rio de Janeiro (UERJ), Brazil
Alexandre Solon Nery - Universidade do Estado do Rio de Janeiro (UERJ), Brazil
Aline de Paula Nascimento - Universidade Federal Fluminense (UFF), Brazil
Andrew Putnam - Microsoft, USA
Carla Osthoff - Laboratório Nacional de Computação Científica (LNCC), Brazil
Cristina Boeres - Universidade Federal Fluminense (UFF), Brazil
Diego Dutra - Universidade Federal do Rio de Janeiro (UFRJ), Brazil
Edson Borin - Universidade Estadual de Campinas (UNICAMP), Brazil
Elias Mizan - Synaptics, USA
Emilio Francesquini - Universidade Estadual de Campinas (UNICAMP), Brazil
Eugene Vinod - Universidade Federal Fluminense (UFF), Brazil
Francisco Sant'Anna - Universidade do Estado do Rio de Janeiro (UERJ), Brazil
Gabriele Mencagli - University of Pisa, Italy
Gabriel Paillard - Universidade Federal do Ceará (UFC), Brazil
Guido Araújo - UNICAMP, Brazil
Hung Wei Tseng – North Carolina State University, USA
Igor Machado Coelho - Universidade do Estado do Rio de Janeiro (UERJ), Brazil
Inês Dutra - Universidade do Porto, Portugal
Lúcia Drummond - Universidade Federal Fluminense (UFF), Brazil
Marcelo Zamith - Universidade Federal Rural do Rio de Janeiro (UFRRJ), Brazil
Maria Clicia Stelling de Castro - Universidade do Estado do Rio de Janeiro (UERJ), Brazil
Maurício Pilla - Universidade Federal de Pelotas (UFPEL), Brazil
Michael Frank - LG Electronics, USA
Nader Bagherzadeh - University of California Irvine, USA
Rafael Burlamaqui Amaral, Centro Federal de Educação Tecnológica do Rio de Janeiro (CEFET-RJ), Brazil
Rafaelli Coutinho, Centro Federal de Educação Tecnológica do Rio de Janeiro (CEFET-RJ), Brazil
Rekai Gonzalez Alberquilla - ARM, UK
Ricardo Farias - Universidade Federal do Rio de Janeiro (UFRJ), Brazil
Sandip Kundu - University of Massachusetts Amherst, USA
Tiago A. O. Alves – Universidade do Estado do Rio de Janeiro (UERJ), Brazil
Ubiratam de Paula - Universidade Federal Rural do Rio de Janeiro (UFRRJ), Brazil
Walid Najjar - University of California Riverside, USA
Zehra Sura - IBM, USA