Multi-device & Multi-backend TornadoVM

20 minute read


This post shows, via examples, how developers can benefit from these features, and reason about performance using the TornadoVM profiler to help us tune our applications.

Running TornadoVM within IntelliJ

4 minute read


Running Java applications from existing IDEs can be a cumbersome process, especially if we need to specify shared libraries. In this post, I will explain how to get access to NVIDIA and Intel-integrated GPUs from IntelliJ using TornadoVM.


Running TornadoVM on NVIDIA Jetson Nano

7 minute read


Did you know that TornadoVM can also run on ARM-based systems with NVIDIA GPUs? In this post, we will show how TornadoVM can be used on an NVIDIA Jetson Nano, a small, powerful computer designed for embedded artificial intelligence (AI) and machine learning (ML) applications.


Enabling Transparent Acceleration of Big Data Frameworks Using Heterogeneous Hardware

21 minute read


Exploiting heterogeneous hardware for Big Data workloads is usually done by introducing new APIs, resulting in more complex programs to develop, understand, and maintain. But, what if we do not change/extend the original programming model? Is it possible? This post discusses a new approach to do so.

Exploring Level Zero resources: repositories and purpose

2 minute read


Sometimes, it is not clear which Level Zero repository is the right one for our needs. In this post, we will explain each of the Level Zero public resources and what they are intended to be.

Installing CUDA, OpenCL and Level Zero in OpenSUSE Leap 15

6 minute read


In this post, we show how to install the NVIDIA drivers to get access to CUDA and OpenCL parallel programming frameworks and utilities for NVIDIA GPUs. We also show how to install the Intel compute-runtime drivers for accessing, via OpenCL and Level Zero, Intel Integrated Graphics.