10 Jun


Figure 1: AI + RV / Visualizing Deep Learning Results on vGTD Platform with Laptop

Novaglobal is delivering a vGPU Training & Development Platform solution based on NVIDIA Tesla T4, Virtual GPU (vGPU) and NVDOCKER supported with NVIDIA GPU CLOUD (NGC). The platform will focus on providing GPU readied solutions for:

  1. AI / Deep Learning
  2. HPC Applications
  3. 3D Remote Visualization
  4. Digital Rendering / VR

Key benefits of system:

  1. Open Source solution except for NVIDIA vGPU licences
  2. Support for up to 32 vGPU instances concurrently
  3. With vGPU template, VM can be built up to support DL teaching environment very quickly
  4. Support all major DL frameworks
  5. Support Windows & various flavours of Linux.
  6. Does not require VDI. GUI/RV is built-in with VM.
  7. Supported with DOCKER/NVDOCKER for fast deployment
  8. Integrated to NVIDIA GPU CLOUD (NGC)

Hardware Requirements:

  • ASUS 4U ESC8000 G4 GPU Server
  • Dual Intel CPU
  • 384GB System RAM
  • 4 x SSD
  • 8 x NVIDIA Tesla T4
28 Feb


Watching over the health of your DGX System!

Video 1: DGX-1 System Monitoring Overview

Figure 1: Dashboard – Hardware Information
Figure 2: Dashboard – Resource Information
Figure 3: Dashboard – GPU Temperatures
Figure 4: Email Alert Notification
25 Oct


Over the past few months, NovaGlobal has the good fortune in working closely with NTU – Earth Observatory of Singapore (EOS) and NASA Jet Propulsion Laboratory (NASA JPL) Team to migrate the Hybrid Cloud Science Data System (HySDS) Framework from Amazon AWS to Azure Cloud Platform. This exercise is to provide another dependable alternative computing resources to support the Advanced Rapid Imaging and Analysis (ARIA) Project.

ARIA Project focus on Natural Hazards to bring geodetic imaging and analysis capabilities to an operational level in support of local, national, and international hazard response communities.

Interferogram is one of the products that can be generated through the HySDS system. By monitoring satellite data acquired over a specified region, the system can automatically generate interferograms comparing displacement on two or more dates. These automatic products are formed from a pre-determined set of rules that define imaging parameters such as range and azimuth looks, temporal baseline, and pairing direction.

We are successful in our mission! Please enjoy the beautiful images of our beloved Singapore from space.

Date of images: circa August 2018

The different colors in an interferogram show changes in the phase of radar waves before and after a seismic event e.g. an earthquake. The colored contours represent the interference fringes between the two sets of data.

The HySDS system is, in fact, a High Performance Computing Cluster (HPCC) implementation in the Cloud. HySDS can use a heterogeneous set of worker nodes from private & public Clouds as well as virtual & bare-metal machines to perform every aspect of the traditional science data system.

“Hybrid Cloud Science Data System Framework”. NASA JPL. Retrieved 25 October 2018.
“How InSAR Works”. Centre for the Observation and Modelling of Earthquakes, Volcanoes and Tectonics. Retrieved 25 October 2018.