activity
20232025
most citedA Data-Driven Approach to Lightweight DVFS-Aware Counter-Based Power Modeling for Heterogeneous Platforms

5 citations · 10 across the 5 of their papers we have counts for

collaborators

5 papers

cs.PF20255 cited

Data-Driven Power Modeling and Monitoring via Hardware Performance Counter Tracking

Sergio Mazzola, Gabriele Ara, Thomas Benz +3

Energy-centric design is paramount in the current embedded computing era: use cases require increasingly high performance at an affordable power budget, often under real-time const…

cs.AR2025

MemPool Flavors: Between Versatility and Specialization in a RISC-V Manycore Cluster

Sergio Mazzola, Yichao Zhang, Marco Bertuletti +2

As computational paradigms evolve, applications such as attention-based models, wireless telecommunications, and computer vision impose increasingly challenging requirements on com…

cs.AR2024

Enabling Efficient Hybrid Systolic Computation in Shared L1-Memory Manycore Clusters

Sergio Mazzola, Samuel Riedel, Luca Benini

Systolic arrays and shared-L1-memory manycore clusters are commonly used architectural paradigms that offer different trade-offs to accelerate parallel workloads. While the first e…

cs.PF2024

Data-Driven Power Modeling and Monitoring via Hardware Performance Counters Tracking

Sergio Mazzola, Gabriele Ara, Thomas Benz +3

In the current high-performance and embedded computing era, full-stack energy-centric design is paramount. Use cases require increasingly high performance at an affordable power bu…

cs.PF20235 cited

A Data-Driven Approach to Lightweight DVFS-Aware Counter-Based Power Modeling for Heterogeneous Platforms

Sergio Mazzola, Thomas Benz, Björn Forsberg +1

Computing systems have shifted towards highly parallel and heterogeneous architectures to tackle the challenges imposed by limited power budgets. These architectures must be suppor…