Field Programmable GateInstructions for building one :)
Acceleration of Algorithms using FPGAs and GPUs
Research in the Reconfigurable and GPU Computing Laboratory (RCL) investigates the use of Accelerators such as Field Programmable Gate Arrays (FPGAs) and Graphics Processing Units (GPUs) for scientific applications. Our interest is in developing libraries and interfaces that make acceleration easier to use. In GPU research, we are investigating how best to take advantage of GPUs from common programming environments such as Matlab and SCIRun. We are also looking at Tasks and Conduits as a mechanism for mapping the same application to several different target hardware platforms.
Our FPGA projects include using OpenCPI as a component model for FPGA
research. In addition, we have developed a widely used
variable precision floating point library (VFLOAT).
In the lab
we use a combination of research and commercial tools, as well as the
software and hardware needed to map designs onto field programmable logic.
Reconfigurable and GPU Computing Lab Links
- Professor Miriam Leeser (mel at coe.neu.edu)
- Research Projects
- Lab Members (including graduated students with links to theses)
- Lab Resources
Funding and Donations
Research Funding in The RCL comes from:
- Mathworks (2007-2016)
- Mathworks SMART (System Modeling and Radio Technology) Lab
- MIT Lincoln Laboratory via the Lincoln Scholars Program.
- National Science Foundation (2012-2015): Ensuring Reliability and Portability of Scientific Software for Heterogeneous Architectures
- NVIDIA Teaching Center
- Mercury Federal Systems(2010-2011)
- NSF: A Biomedical Imaging Acceleration Testbed (2009-2012)