Abstract: The minimization of losses through a simultaneous network reconfiguration (NR), capacitor placement (CP) and distributed generation (DG) allocation under varying loading conditions is a ...

Current mainstream KV cache optimization techniques (quantization and pruning) suffer from "one-size-fits-all" limitations and cannot fully exploit the fine-grained differences within the KV cache.

When using VS Code Jupyter notebooks, variables (like large pandas DataFrames, NumPy arrays, or ML models) can consume a lot of memory, but it’s not obvious how much each one uses, which can lead to ...

Abstract: As the scaling of memory density slows physically, a promising solution is to scale memory logically by enhancing the CPU's memory controller to encode and store data more densely in memory.