Our strategical axes

The institute’s work is organised along three lines of research. The following buttons will show you the assigned projects for each line.

 

Efficient Information Processing

Axis coordinator: Yann Thoma

Our skills in the field of programmable circuits (FPGA/CPLD) and interconnection technologies (high-speed interfaces and buses) lead to innovative solutions in the domain of applications requiring high-speed data processing (hardware acceleration, signal processing, cryptography, etc.).
 
Our realizations rely on a solid experience of digital systems development and verification methodologies (VHDL, SystemVerilog, EDA tools, Matalab Simulink).
 
  • Computing accelerator
  • Hardware implementation tailored to dedicated algorithms (Cryptography, signal processing, etc.)
  • High-speed data communication
  • Co-design and data flow optimization
  • Software for hardware design

Under development


PoSeNoGap

May 2, 2014, 15:23 PM
Portable Scalable Concurrency for Genomic Data Processing
Page:
ce38664f-169f-6184-b062-ff0000b5cb90
Select a choice:
Terminated
StartDate:
Feb 1, 2014, 00:00 AM
EndDate:
Jun 30, 2017, 00:00 AM

PoSeNoGap aims at designing a new framework for managing big genomic data. Sequencing a human genome outputs around 300GB of raw data. Compressing these data is necessary and requires computing resources. Analyzing these data also is very time consumming. Therefore within this project the team will develop new approaches for both compression and analysis of genomic data. Within this context, the REDS is developing an efficient solution for clustering unmapped sequences thanks to a high-end FPGA platform.

axes:
  • Software-oriented Heterogeneous Device Support
  • Hardware-oriented Efficient Information Processing
domaines-d-application:
  • Health
Tags:

Completed projects


PoSeNoGap

May 2, 2014, 15:23 PM
Portable Scalable Concurrency for Genomic Data Processing
Page:
ce38664f-169f-6184-b062-ff0000b5cb90
Select a choice:
Terminated
StartDate:
Feb 1, 2014, 00:00 AM
EndDate:
Jun 30, 2017, 00:00 AM

PoSeNoGap aims at designing a new framework for managing big genomic data. Sequencing a human genome outputs around 300GB of raw data. Compressing these data is necessary and requires computing resources. Analyzing these data also is very time consumming. Therefore within this project the team will develop new approaches for both compression and analysis of genomic data. Within this context, the REDS is developing an efficient solution for clustering unmapped sequences thanks to a high-end FPGA platform.

axes:
  • Software-oriented Heterogeneous Device Support
  • Hardware-oriented Efficient Information Processing
domaines-d-application:
  • Health
Tags: