Deep Dive: Accelerating Neural Networks using RVV and Open Standard Software - Mehdi Goli, Codeplay

Deep Dive: Accelerating Neural Networks using RVV and Open Standard Software - Mehdi Goli, Codeplay Software Neural Networks are foundational AI constructs for recognizing relationships in data requiring processing massive datasets in the form of tensors. Tensor processing is central to AI and machine learning applications. The RISC-V Vector (RVV) extension provides the capacity to accelerate computation of these tensor datasets in parallel on multi core processors. However, the extension alone provides only a part of the solution with software developers needing a standard programming interface targeting RVV for data intensive operations and host CPU for latency-sensitive operations. This presentation will dive in detail how our team accelerated the execution of a tensor-based neural network on the Spike simulator using open source and open standard software. The journey begins at the driver level where we implemented low-level abstractions, then moves to modifications made to extend the LLVM compiler, on t