2 citations · 2 across the 2 of their papers we have counts for
3 papers
Architecting for Hardware Diversity: Meta's End-to-End Co-Design for High-Performance AI Training on AMD GPUs
Haoyu Zhang, Arshad Rahman, Adnan Aziz +55
Meta deploys a heterogeneous fleet comprising NVIDIA GPUs, AMD GPUs, and proprietary MTIA accelerators to reduce costs and mitigate vendor lock-in. However, the extensive history o…
ZeRO-Prefill: Zero Redundancy Overheads in MoE Prefill Serving
Zhaoyuan Su, Olatunji Ruwase, Karthik Ganesan +5
Production LLM workloads increasingly serve discriminative tasks, such as classification, recommendation, and verification, whose answers are read from the logits of a single prefi…
BlackJack: Secure machine learning on IoT devices through hardware-based shuffling
Karthik Ganesan, Michal Fishkin, Ourong Lin +1
Neural networks are seeing increased use in diverse Internet of Things (IoT) applications such as healthcare, smart homes and industrial monitoring. Their widespread use makes neur…