most citedNQC2: A Non-Intrusive QEMU Code Coverage Plugin

2 citations · 3 across the 2 of their papers we have counts for

collaborators

5 papers

cs.SE20262 cited

NQC2: A Non-Intrusive QEMU Code Coverage Plugin

Nils Bosbach, Alwalid Salama, Lukas Jünger +4

Code coverage analysis has become a standard approach in software development, facilitating the assessment of test suite effectiveness, the identification of under-tested code segm…

cs.LG2026

Mixed-Precision Training and Compilation for RRAM-based Computing-in-Memory Accelerators

Rebecca Pelke, Joel Klein, Jose Cubero-Cascante +3

Computing-in-Memory (CIM) accelerators are a promising solution for accelerating Machine Learning (ML) workloads, as they perform Matrix-Vector Multiplications (MVMs) on crossbar a…

cs.SE20251 cited

High-Performance ARM-on-ARM Virtualization for Multicore SystemC-TLM-Based Virtual Platforms

Nils Bosbach, Rebecca Pelke, Niko Zurstraßen +3

The increasing complexity of hardware and software requires advanced development and test methodologies for modern systems on chips. This paper presents a novel approach to ARM-on-…

cs.AR2025

Introducing Instruction-Accurate Simulators for Performance Estimation of Autotuning Workloads

Rebecca Pelke, Nils Bosbach, Lennart M. Reimann +1

Accelerating Machine Learning (ML) workloads requires efficient methods due to their large optimization space. Autotuning has emerged as an effective approach for systematically ev…

eess.SP2025

Evaluating the Scalability of Binary and Ternary CNN Workloads on RRAM-based Compute-in-Memory Accelerators

José Cubero-Cascante, Rebecca Pelke, Noah Flohr +3

The increasing computational demand of Convolutional Neural Networks (CNNs) necessitates energy-efficient acceleration strategies. Compute-in-Memory (CIM) architectures based on Re…