activity
20192026
most citedPOD-Attention: Unlocking Full Prefill-Decode Overlap for Faster LLM Inference

20 citations · 28 across the 7 of their papers we have counts for

collaborators

8 papers

cs.DB2026

The Case for TPU-Accelerated Analytical Query Processing

Yeounoh Chung, Jaehyun Ha, Helena Caminal +4

Large-scale analytical query processing requires computing substrates capable of immense distributed scale-out. Tensor Processing Units (TPUs) perfectly embody this extreme-scale a…

cs.LG2026

Reducing the GPU Memory Bottleneck with Lossless Compression for ML -- Extended

Aditya K Kamath, Arvind Krishnamurthy, Marco Canini +1

Machine learning (ML) training and inference often process data sets far exceeding GPU memory capacity, forcing them to rely on PCIe for on-demand tensor transfers, causing critica…

cs.LG2026

LLM-42: Enabling Determinism in LLM Inference with Verified Speculation

Raja Gond, Aditya K Kamath, Ramachandran Ramjee +1

In LLM inference, the same prompt may yield different outputs across different runs. At the system level, this non-determinism arises from floating-point non-associativity combined…

cs.LG2024★ 20 cited

POD-Attention: Unlocking Full Prefill-Decode Overlap for Faster LLM Inference

Aditya K Kamath, Ramya Prabhu, Jayashree Mohan +3

Each request in LLM inference goes through two phases: compute-bound prefill and memory-bandwidth-bound decode. To improve GPU utilization, recent systems use hybrid batching that…

cs.CY2024★ 2 cited

LLeMpower: Understanding Disparities in the Control and Access of Large Language Models

Vishwas Sathish, Hannah Lin, Aditya K Kamath +1

Large Language Models (LLMs) are a powerful technology that augment human skill to create new opportunities, akin to the development of steam engines and the internet. However, LLM…

cs.OS2024

Herding LLaMaS: Using LLMs as an OS Module

Aditya K Kamath, Sujay Yadalam

Computer systems are becoming increasingly heterogeneous with the emergence of new memory technologies and compute devices. GPUs alongside CPUs have become commonplace and CXL is p…

cs.OS2023★ 1 cited

MaxMem: Colocation and Performance for Big Data Applications on Tiered Main Memory Servers

Amanda Raybuck, Wei Zhang, Kayvan Mansoorshahi +3

We present MaxMem, a tiered main memory management system that aims to maximize Big Data application colocation and performance. MaxMem uses an application-agnostic and lightweight…

cs.AR2019★ 5 cited

Storage Class Memory: Principles, Problems, and Possibilities

Aditya K Kamath, Leslie Monis, A Tarun Karthik +1

Storage Class Memory (SCM) is a class of memory technology which has recently become viable for use. Their namearises from the fact that they exhibit non-volatility of data, simila…