autoregressive drift 1clifford+t optimization 1edge llm inference 1energy-efficient computing 1fault-tolerant computing 1gpu-npu co-execution 1heterogeneous scheduling 1micro-batching 1quantum circuit synthesis 1transformer models 1
From the 2 of 3 linked papers with an AI index.
3 papers
cs.DC2026
HeteroMosaic: Exposing and Exploiting Heterogeneous Execution Opportunities for Energy-Efficient Edge LLM Inference
Gregory Hyegang Jun, Wesley Pang, Eddie Richter +4
The paper introduces HeteroMosaic, a scheduling framework that coordinates CPUs, integrated GPUs, and NPUs on edge SoCs to run large language model inference more quickly and with…
quant-ph2026
When Close Enough Is Not Enough: Autoregressive Drift in Quantum Circuit Synthesis
Mehdi Saeedi, Eddie Richter, Paul Hartke
The paper studies using a large encoder‑decoder transformer to synthesize fault‑tolerant quantum circuits, showing it works well when post‑processing can correct continuous paramet…
cs.CL2025
From Loop Nests to Silicon: Mapping AI Workloads onto AMD NPUs with MLIR-AIR
Erwei Wang, Samuel Bayliss, Andra Bisca +19
General-purpose compilers abstract away parallelism, locality, and synchronization, limiting their effectiveness on modern spatial architectures. As modern computing architectures…