5 papers
Fine-Tuning a 3B-Parameter LLM on a Smartphone: Characterizing Sustained Training
Andrew Geyko, Marius Mosbach, André Brinkmann
Multi-billion-parameter LLMs now run on phones for inference, and training them on the device would personalize them without user data leaving the phone. Prior work has measured in…
Efficient LLM-Generated Shuttling Compilers for Complex Trapped-Ion Architectures
Fabian Kreppel, Reza Salkhordeh, Ferdinand Schmidt-Kaler +1
Trapped-ion quantum computers rely on shuttling compilers, which cast an input algorithm into a sequence of ion-qubit movements within a given architecture. We present the first st…
Employ SmartNICs' Data Path Accelerators for Ordered Key-Value Stores
Frederic Schimmelpfennig, Jan Sass, Reza Salkhordeh +3
Remote in-memory key-value (KV) stores serve as a cornerstone for diverse modern workloads, and high-speed range scans are frequently a requirement. However, current architectures…
Shuttling Compiler for Trapped-Ion Quantum Computers Based on Fine-Tuned Large Language Models
Fabian Kreppel, Reza Salkhordeh, Ferdinand Schmidt-Kaler +1
In trapped-ion quantum computers, qubits must be shuttled between segments to interact. The routing logic that schedules these movements is written by hand for every new trap archi…
Skip TLB flushes for reused pages within mmap's
Frederic Schimmelpfennig, André Brinkmann, Hossein Asadi +1
Memory access efficiency is significantly enhanced by caching recent address translations in the CPUs' Translation Lookaside Buffers (TLBs). However, since the operating system is…