most citedReclaimer: A Reinforcement Learning Approach to Dynamic Resource Allocation for Cloud Microservices

2 citations · 3 across the 8 of their papers we have counts for

collaborators

8 papers

cs.AR2024

iMIV: in-Memory Integrity Verification for NVM

Rajat Jain, Aravinda Prasad, Sreenivas Subramoney +1

Non-volatile Memory (NVM) could bridge the gap between memory and storage. However, NVMs are susceptible to data remanence attacks. Thus, multiple security metadata must persist al…

cs.AR2024

Constable: Improving Performance and Power Efficiency by Safely Eliminating Load Instruction Execution

Rahul Bera, Adithya Ranganathan, Joydeep Rakshit +8

Load instructions often limit instruction-level parallelism (ILP) in modern processors due to data and resource dependences they cause. Prior techniques like Load Value Prediction…

cs.CL2024

QCQA: Quality and Capacity-aware grouped Query Attention

Vinay Joshi, Prashant Laddha, Shambhavi Sinha +2

Excessive memory requirements of key and value features (KV-cache) present significant challenges in the autoregressive inference of large language models (LLMs), restricting both…

cs.OS2024

Taming Server Memory TCO with Multiple Software-Defined Compressed Tiers

Sandeep Kumar, Aravinda Prasad, Sreenivas Subramoney

Memory accounts for 33 - 50% of the total cost of ownership (TCO) in modern data centers. We propose a novel solution to tame memory TCO through the novel creation and judicious ma…

cs.AR2024

CiMNet: Towards Joint Optimization for DNN Architecture and Configuration for Compute-In-Memory Hardware

Souvik Kundu, Anthony Sarah, Vinay Joshi +2

With the recent growth in demand for large-scale deep neural networks, compute in-memory (CiM) has come up as a prominent solution to alleviate bandwidth and on-chip interconnect b…

cs.OS2023

Motivating Next-Generation OS Physical Memory Management for Terabyte-Scale NVMMs

Shivank Garg, Aravinda Prasad, Debadatta Mishra +1

Software managed byte-addressable hybrid memory systems consisting of DRAMs and NVMMs offer a lot of flexibility to design efficient large scale data processing applications. Opera…