Tech Fee Hosted Equipment

The Georgia Tech TechFee program provides an opportunity for GT faculty and staff to submit proposals on behalf of instructors and students for resources that are dedicated to classroom educational and research experiences. These TechFee proposals are funded via student technology fees, so their primary purpose is to provide novel equipment that helps to further student instructional and unfunded (ie, undergraduate) research aims. CRNCH is proud to help utilize our expertise in supporting novel accelerators to provide access to TechFee-funded equipment for class and student usage.

Note: If you are an instructor looking to use these resources for a course, please email the PI, Jeffrey Young with information on your class use case. If you are a GT student, you can request an account on the Rogues Gallery using the online form.

Funded TechFee Proposals Hosted by Rogues Gallery

 

FY 2020 - Reconfigurable Cluster Initiative

Funded amount: $74,905

PIs:  Jeffrey Young, Hyesoon Kim, Jason Riedy, Lee Lerner

Proposed Overview: This initiative proposes to acquire up to nine Field Programmable Reconfigurable Array (FPGA) devices and two host servers to seed a new reconfigurable cluster initiative. This cluster will initially be used by Atlanta-based students in multiple courses but will eventually be extended to support a limited number of OMSCS students via remote access and cluster-based scheduling. We anticipate supporting undergraduate students and graduate students for coursework as well as making the resource available to all interested students via our existing TSO-supported testbed, the “Rogues Gallery”. This effort will provide easier access to novel hardware for students as well as reduce the need for individual professors to acquire and maintain this type of hardware for their classes.

Status Update: Due to the COVID-19 pandemic, remote access to novel FPGA hardware has become more critical than ever. CRNCH has pushed ahead with supporting devices that can be remotely accessed and power cycled. All of our deployed equipment can be accessed from off campus by enrolled students, and we are working on Slurm scheduling to support larger class usage.

Thanks to: Tool support is provided by Intel donations and the Xilinx University Program (XUP). Many thanks also to the XUP program for the donation of U280 cards for research and teaching support.

 

What’s available for class and student use?:

FPGA Board / DevKit
FPGA
Memory
Programming Tools
Notes
Hosting Machine
GX1150
8 GB DDR4
Intel SDK, OneAPI
 
Flubber
Intel Stratix 10 PAC Coming soon 16 GB DDR3   Coming soon Flubber  
Bittware 520N-MX GX2800 16 GB DDR4 Intel SDK, OpenCL   Flubber
Mellanox Innova-2 Flex SmartNIC Kintex Ultrascale XCKU15P 8 GB DDR4 Xilinx Vivado Connect-X 5 SmartNICs with FPGA chips Flubber
Zynq XC7Z020-1CLG400C
512MB DDR3
Xilinx Vivado, PYNQ
Also available for Nengo-FPGA
Brainard
Zynq UltraScale+ MPSoC XCZU7EV-1FBVB900E
DDR4
Xilinx Vitis, Vivado
 
Brainard
Zynq UltraScale+ MPSoC Evaluation Kit Zynq Ultrascale+ MPSoC XCZU7EV-2FFVC1156 DDR4, 4 GB Xilinx Vitis, Vivado, PYNQ   Brainard
Ultrascale+ XCU280
8 GB HBM2
Xilinx Vitis, Vivado, Vitis AI
Supported in part by XUP
Flubber, multiple cards
Raspberry Pi 4 Used to host FPGA Devkits 4 GB DDR2 OpenMP Used to support PYNQ and devkit usage Brainard
Coral TPU Quad Cortex-A53, Cortex-M4F, Google Edge TPU 1 GB LPDDR4 TensorFlow Lite Devkit that allows for alternate AI comparisons with TPU units. Brainard
Intel Movidius Neural Stick 2     OpenVino Devkit that allows for alternate AI comparisons Brainard
Jetson Xavier NX 6-core Arm Carmel CPU, 384 V100 cores 8 GB DDR4 OpenMP, CUDA Devkit that allows for alternate AI comparisons Brainard

What classes have made use of this resource?

Please note that this list may change as resources must typically be deployed one semester before class usage.

  • ECE 2601, 3601, 4601 (VIP)
  • CS 3220
  • CS 2698/4698 (Undergraduate Research)
  • As of Fall 2020, ~35 students have access to the CRNCH reconfigurable resources for academic-related projects.

Additionally we are seeking opportunities to utilize this hardware for machine learning-related classes like  CS 4803 / 7643 and digital design classes like ECE 2031. Special topics projects like CS8803 (Topics on Datacenter Design, Dr. Alex Daglis) also are planned to make use of Xilinx-based smartNICs for optional class projects.

Tools Available: Intel FPGA SDK 2019 (19.3, 20.1), Intel Devstack, Xilinx Vitis and Vivado 19.2, 20.1, Xilinx PYNQ

Primary Contact: Jeffrey Young

Restrictions: Techfee equipment is prioritized for instructional usage. General student usage can occur on an ad-hoc basis but is scheduled at a lower priority.