78 citations · 184 across the 24 of their papers we have counts for
4 papers · 1 filter
Stella Nera: A Differentiable Maddness-Based Hardware Accelerator for Efficient Approximate Matrix Multiplication
Jannis Schönleber, Lukas Cavigelli, Matteo Perotti +2
Artificial intelligence has surged in recent years, with advancements in machine learning rapidly impacting nearly every area of life. However, the growing complexity of these mode…
Ara2: Exploring Single- and Multi-Core Vector Processing with an Efficient RVV 1.0 Compliant Open-Source Processor
Matteo Perotti, Matheus Cavalcante, Renzo Andri +2
Vector processing is highly effective in boosting processor performance and efficiency for data-parallel workloads. In this paper, we present Ara2, the first fully open-source vect…
Flex-SFU: Accelerating DNN Activation Functions by Non-Uniform Piecewise Approximation
Enrico Reggiani, Renzo Andri, Lukas Cavigelli
Modern DNN workloads increasingly rely on activation functions consisting of computationally complex operations. This poses a challenge to current accelerators optimized for convol…
MemPool: A Scalable Manycore Architecture with a Low-Latency Shared L1 Memory
Samuel Riedel, Matheus Cavalcante, Renzo Andri +1
Shared L1 memory clusters are a common architectural pattern (e.g., in GPGPUs) for building efficient and flexible multi-processing-element (PE) engines. However, it is a common be…