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APEX achieves over 99% overlap accuracy in expert prefetching, slashing per-token latency by up to 26% while enhancing energy efficiency for edge MoE inference.
Voltage droop violations are tackled with a 76x reduction in energy-delay product, all while keeping ML inference accuracy intact.
Hybrid Mamba-Transformer models can get 4x faster time to first token and 1.4x higher throughput by disaggregating prefill and decode phases onto specialized accelerator packages.
LLMs can run up to 35% faster on chiplet architectures thanks to a new lossless exponent compression technique that slashes inter-chiplet communication overhead.
