With some help from our students (Zhengyu Xu) and Karim (Karim Ben Kalia) we have put up a Heterogeneous Computing Cluster, called GAGA (GPU And Gate Array) cluster. Yeah, sorry for the name. While this is not the first cluster of this type, GAGA is a bit different. It is an embedded super-computing cluster, i.e the whole software stack is rebuilt given the application, and it runs only one application at a time. In the spirit of embedded computing, everything (Linux kernel, MPI, OpenCL, FPGA hardware) is tuned to a technical context.

Hardware

• DE1-SoC Boards from Terasic, with cyclone V SoCFPGA from Altera (ARM Cortex A9 (Dual core) Hard Processor System 925 MHz, 85K LUT FPGA, 1GB DDR3 SDRAM.

• ODROID-XU board from Hardkernel [3], with Exynos Octa SoC (ARM Cortex A15/A7 (quad core) and PowerVR/Mali embedded GPUs, 2GB LPDDR3).

• HP Procurve 2530G PoE+ switch. (24 1Gb ports, 4 SFP ports, Switching Capacity 56 Gbps, PoE power capability 195 Watts,

Software

Only the libraries necessary for a given technical context goes on-board. The whole executable software can be contained within 10MBytes, which allows fast booting, wake-up and more resources dedicated to applications.

Software Stack	Build System
Linux Kernel	Kernel Config
InitRamFS	Buildroots
MPICH	GCC X-Compile
FPGA OpenCL Runtime	Altera OpenCL SDK
GPU OpenCL Runtime	PowerVR GPU Compute
Custom Libraries e.g BLAS	GCC X-Compile