JavaWrite Once, Accelerate Everywhere: GPU-Ready Java with TornadoVM
This talk introduces TornadoVM, an open-source framework that enables seamless GPU, CPU, and FPGA acceleration for Java applications without requiring GPU-specific code. It covers TornadoVM’s key features, practical optimization techniques, live coding demos, and showcases how it accelerates AI workloads like GPULlama3.java using only Java.
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In the AI era, accessing GPUs from Java is essential - but it still remains a challenge. TornadoVM bridges this gap by enabling developers to accelerate Java applications on GPUs, CPUs, and FPGAs without writing any GPU code. Originally born as a PhD research project at the University of Manchester, TornadoVM has evolved into a mature open-source framework supported by both academia and a growing global community.
This talk will present the key innovations that are offered by the TornadoVM runtime platform, and will focus on practical ways to optimize existing Java applications through its high-level API. Through hands-on examples, we will demonstrate how to offload computations, manage data efficiently, and achieve significant performance gains - entirely from Java.
We will also showcase GPULlama3.java, a pure Java large language model (LLM) library accelerated with TornadoVM, illustrating how modern AI workloads can run efficiently within the JVM. Finally, a live-coding demo using IntelliJ IDEA will highlight TornadoVM’s integrated profiling and tooling ecosystem for seamless development experience.
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