One TPU Chip, Eight Agents: Serving Small Agent Workloads with Raw JAX
Cloud TPU v6e-1 ( ct6e-standard-1t , one v6e chip, 32 GB HBM), GCE flex-start, europe-west4-a. vLLM baseline measured 2026-07-21. The workload nobody …
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Large-Scale TensorCircuit Contractions on GPUs: Disabling XLA GPU Autotuning
When running large-scale tensor-network contractions with TensorCircuit-NG and the JAX GPU backend, the following runtime configuration is worth testi…
PyTrees Are Not One Thing: JAX, PyTorch, and TensorFlow Compared
PyTrees look deceptively simple. You flatten a nested Python object into leaves, keep a structure descriptor, and later rebuild or map over the same s…
Why JAX Is a Much Better Backend for Quantum Circuit Simulation Than PyTorch
Modern quantum circuit simulation is not just “machine learning with complex tensors.” It involves irregular tensor contractions, sparse operators, st…