VSAONLINE-10. Marco Angioli and Rocco Martino
Evgeny Osipov
Dear all,
Welcome to the next talk on VSAONLINE by Marco Angioli and Rocco Martino from Sapienza Università di Roma, Italy!
Date: February 24, 2025
Time: 20:00 GMT
Zoom: https://ltu-se.zoom.us/j/65564790287
Two talks session: Reinforcement Learning with Hyperdimensional Computing on Flexible Hardware:
From Contextual Bandits Problems to Configurable Hardware Acceleration on RISC-V
February 24, 2025. 20:00GMT
Marco Angioli and Rocco Martino, Sapienza Università di Roma, Italy
Abstract 1: This talk introduces HD-CB, the first application of Hyperdimensional Computing to model and automate sequential decision-making in Contextual Bandits problems. HD-CB maps environmental states into a high-dimensional space, representing actions with dedicated hypervectors that are updated in real-time based on received rewards. By operating directly in the high-dimensional space, HD-CB replaces traditional, computationally expensive methods, like ridge regression, with efficient and highly parallel vector operations, achieving superior performance, faster convergence, and improved scalability.
Abstract 2: With its inherent parallelism, Hyperdimensional Computing is an ideal candidate for hardware implementation. This talk introduces HDCU, a reconfigurable hardware accelerator powered by a novel RISC-V instruction set extension. HDCU accelerates core arithmetic operations on hypervectors and can be configured at synthesis time to balance execution speed and resource usage, adapting to diverse applications. A custom RISC-V Instruction Set Extension is designed to efficiently control the accelerator, with instructions fully integrated into the GCC compiler chain and exposed to the programmer as intrinsic function calls. The dual flexibility coming from hardware configuration and software programmability sets this work apart from application-specific solutions in the literature, offering a unique, versatile accelerator adaptable to a wide range of applications and learning tasks.
Best,
Evgeny