Latest News/Update

Major Revision of the Variable Precision FLOATing point library (VFLOAT)
Released December 2013. This new version of the VLOAT library adds a new reciprocal unit as well as fixing bugs from previous versions. All components have been tested with Altera and Xilinx IDEs.

Xin Fang successfully defends his MS thesis, Variable Precision Floating Point Reciprocal, Divider and Square Root for Major FPGA Vendors, July 2013.

National Science Foundation funds project: MRI: Development of a testbed for side channel analysis and security evaluation (TeSCASE)

Jonathan Pendlum contributes to the FPGA Accelerators in GNU Radio with Xilinx's Zynq System on Chip project.

Peter Grossman successfully defends his PhD, Design and Analysis of Minimum Energy FPGAs, April 2013.

David Kusinsky successfully defends his MS thesis, FPGA-based Hyperspectral Covariance Coprocessor for Size, Weight, and Power Constrained Platforms, April 2013.

Mathworks SMART (System Modeling and Radio Technology) Lab is officially open.

Northeastern becomes a NVIDIA Teaching Center.

Software now available for CT Reconstruction Acceleration on GPUs.

Field Programmable Gate Array

Field Programmable Gate

Instructions 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

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Funding and Donations

Research Funding in The RCL comes from:

We would like to thank the companies who donate hardware and software to the RCL: