36 citations · 124 across the 26 of their papers we have counts for
4 papers · 1 filter
OptiNIC: A Resilient and Tail-Optimal RDMA NIC for Distributed ML Workloads
Ertza Warraich, Ali Imran, Annus Zulfiqar +3
As distributed machine learning (ML) workloads scale to thousands of GPUs connected by high-speed interconnects, tail latency in collective communication has become a major bottlen…
Reimagining RDMA Through the Lens of ML
Ertza Warraich, Ali Imran, Annus Zulfiqar +3
As distributed machine learning (ML) workloads scale to thousands of GPUs connected by ultra-high-speed inter-connects, tail latency in collective communication has emerged as a pr…
Counter Pools: Counter Representation for Efficient Stream Processing
Ran Ben Basat, Gil Einziger, Bilal Tyah +1
Due to the large data volume and number of distinct elements, space is often the bottleneck of many stream processing systems. The data structures used by these systems often consi…
HACK: Homomorphic Acceleration via Compression of the Key-Value Cache for Disaggregated LLM Inference
Zeyu Zhang, Haiying Shen, Shay Vargaftik +3
Disaggregated Large Language Model (LLM) inference has gained popularity as it separates the computation-intensive prefill stage from the memory-intensive decode stage, avoiding th…