FPGA/GPU Cluster

The FPGA/GPU cluster is a cloud-based, remotely accessible compute infrastructure specifically designed to accelerate compute-intensive applications, such as machine learning training and inference, video processing, financial computing, database analytics networking and bioinformatics.

The latest state-of-the-art acceleration technologies including the Alveo FPGAs, and Tesla V100 GPUs, closely coupled with server processors constitute the backbone of this cluster. The software stack consists of a complete ecosystem of machine learning frameworks, libraries and runtime targeting heterogeneous computing accelerators.

FPGA/GPU Cluster Software Stack

The FPGA/GPU cluster supports three the most commonly used deep learning frameworks, namely, TensorFlow, Caffe and MXNet. These frameworks provide a high-level abstraction layer for deep learning architecture specification, model training, tuning, testing, and validation. The software stack also includes various machine learning vendor-specific libraries that provide dedicated computing functions tuned for specific hardware architecture, delivering the best possible performance/power figure.

Cluster Software Stack


  • Software IPs and applications targeting ML on heterogeneous computing systems (e.g. CNN, for object detection, speech recognition)
  • Software stack including Parallel programming models, Compilers, Middleware, Runtime, Drivers and OSes
  • Case studies: ML, Big data analytics, data-intensive computing, cybersecurity
  • ASICs Prototyping: e.g., CMOS and other semiconductors, for implementing custom neural network accelerators



  • Secure remote access
  • Machine learning frameworks: Tensorflow, Caffe and MXNet
  • Support for deep learning training and inference
  • Customizability: Select the right combination of accelerators for your application
  • Reference designs using software stack for OpenCL, MPI heterogenous cluster computing
  • Scalability: Create one node neural network graph and scale up by using more nodes
  • Fast automated setup and configuration

Who Can Access

Canadian Academic Subscribers

– or –

VIE Members

Contact Us

Dr. Yassine Hariri
Senior Staff Scientist
AI/ML and Embedded Systems

YouTube Channel    Linkedin Group

Does your research benefit from products and services provided by CMC Microsystems?

Open source design platforms for accelerated system development.

Scroll to Top

We use cookies

CMC uses cookies to ensure you get the best experience on our website

Skip to content