In the dense canopies of Central America and the Yucatan, the remains of the ancient Maya civilization are mostly hidden underground, buried by centuries of growing jungle. Many Maya archaeological sites are difficult to access, fragile, and not open to the public. These sites, although instrumental in understanding Maya culture, are seen by very few people. Our goal is to document these sites in order to preserve them digitally, and create visualizations for everyone to virtually visit these wonderful places.

Many Maya archaeological sites are located within the deep jungle of Central America and cannot be visited easily. Additionally, in order to preserve these ancient buildings, tunneling excavations must often be filled back, thus preventing anyone from accessing certain parts of the sites entirely.

Not only do we want to preserve all of these excavations digitally, but we want to share these experiences in the most immersive way possible. Thanks to various data collection methods, using LiDAR, photogrammetry, traditional photographs, sound recording, etc., we are working on combining all the data we have accumulated over the years at the site of El Zotz to create a virtual reality recreation of the numerous excavations.

FPGAs are becoming an important hardware to improve the ratio compute power / energy utilization for many applications. Robotics applications are notably impacted by requiring more processing power for decision making, while often running on limited power. However, designing an efficient application for FPGA is very time-consuming, and a single design can potentially take several hours to map onto the hardware. Each application is usually composed of many parameters that can affect the running time, accuracy, and other desired objectives. Due to the very large space of possible combinations of these parameters, it is often difficult - even for an expert - to predict the outcome of one particular design. We propose smart design space exploration algorithms based on active learning techniques, capable of selecting the most optimal architectures among a pool of possible designs. We also propose tunable FPGA designs to generate and analyze design spaces for multiple applications, and improve the design space exploration methods. We specifically analyze SLAM (Simultaneous Localization And Mapping) design spaces to improve the implementation of such algorithms on FPGA hardware.

High-level synthesis tools allow programmers to use OpenCL to create FPGA designs. Unfortunately, these tools have a complex compilation process that can take several hours to synthesize a single design. Understanding the design space and guiding the optimization process is crucial, but requires a significant amount of design space data that is currently unavailable or difficult to generate. To solve this problem, we have developed Spector, an OpenCL FPGA benchmark suite. We outfitted each benchmark with a range of optimization parameters (or knobs), compiled thousands of unique designs using the Altera OpenCL SDK, and recorded their corresponding performance and utilization characteristics. These benchmarks and results are completely open-source and available on our repository.

We published and presented this work at the ICFPT 2016 conference in Xi'an, China.

This work is based on KinectFusion, a project developed by Microsoft Research. You can use a Kinect camera to reconstruct your environment in 3D in real-time, just by holding the camera and moving around. However this program requires a modern GPU that uses a lot of power. We want to run it on a more power-efficient hardware and hopefully get to 3D reconstruction for embedded systems. We are modifying the open-source version of KinectFusion, Kinfu, to make it run on a FPGA, by using high-level tools such as the Altera OpenCL SDK. The program is divided into three parts: Iterative Closest Point (ICP) for camera motion tracking, Volumetric Integration (VI) to build the 3D model, and Ray Tracing for screen rendering. We have integrated the ICP algorithm on an FPGA to make an hybrid GPU/FPGA application run in real-time, and we are working on optimizing VI to run efficiently on the FPGA.

We published and presented our work at the ICFPT 2014 conference in Shanghai.