Cover Image

Fine-Tuning and Serving Gemma 4 31B on Google Cloud TPU: A Technical Comparison with GPU Baselines

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kishnani, Jatin, Goel, Mayank, Singh, Amit, Agrawal, Pulkit, Mishra, Sairanjan
Format:	Preprint
Published:	2026
Subjects:	Distributed, Parallel, and Cluster Computing Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Revati: Transparent GPU-Free Time-Warp Emulation for LLM Serving
by: Agrawal, Amey, et al.
Published: (2026)

Hetis: Serving LLMs in Heterogeneous GPU Clusters with Fine-grained and Dynamic Parallelism
by: Mo, Zizhao, et al.
Published: (2025)

Predictable LLM Serving on GPU Clusters
by: Darzi, Erfan, et al.
Published: (2025)

ExpertWeave: Efficiently Serving Expert-Specialized Fine-Tuned Adapters at Scale
by: Shi, Ge, et al.
Published: (2025)

ConServe: Fine-Grained GPU Harvesting for LLM Online and Offline Co-Serving
by: Qiao, Yifan, et al.
Published: (2024)

DuaLip-GPU Technical Report
by: Dexter, Gregory, et al.
Published: (2026)

ThunderServe: High-performance and Cost-efficient LLM Serving in Cloud Environments
by: Jiang, Youhe, et al.
Published: (2025)

AgentServe: Algorithm-System Co-Design for Efficient Agentic AI Serving on a Consumer-Grade GPU
by: Zhang, Yuning, et al.
Published: (2026)

Boosting LLM Serving through Spatial-Temporal GPU Resource Sharing
by: Lin, Zejia, et al.
Published: (2025)

Cloud Native System for LLM Inference Serving
by: Xu, Minxian, et al.
Published: (2025)

HydraServe: Minimizing Cold Start Latency for Serverless LLM Serving in Public Clouds
by: Lou, Chiheng, et al.
Published: (2025)

SageServe: Optimizing LLM Serving on Cloud Data Centers with Forecast Aware Auto-Scaling
by: Jaiswal, Shashwat, et al.
Published: (2025)

Dilu: Enabling GPU Resourcing-on-Demand for Serverless DL Serving via Introspective Elasticity
by: Lv, Cunchi, et al.
Published: (2025)

Serving Hybrid LLM Loads with SLO Guarantees Using CPU-GPU Attention Piggybacking
by: Mo, Zizhao, et al.
Published: (2026)

LoHan: Low-Cost High-Performance Framework to Fine-Tune 100B Model on a Consumer GPU
by: Liao, Changyue, et al.
Published: (2024)

ParvaGPU: Efficient Spatial GPU Sharing for Large-Scale DNN Inference in Cloud Environments
by: Lee, Munkyu, et al.
Published: (2024)

Agora: Bridging the GPU Cloud Resource-Price Disconnect
by: McDougall, Ian, et al.
Published: (2025)

Mapping Gemma3 onto an Edge Dataflow Architecture
by: Du, Shouyu, et al.
Published: (2026)

SIMPLE: Disaggregating Sampling from GPU Inference into a Decision Plane for Faster Distributed LLM Serving
by: Zhao, Bohan, et al.
Published: (2025)

PPipe: Efficient Video Analytics Serving on Heterogeneous GPU Clusters via Pool-Based Pipeline Parallelism
by: Kong, Z. Jonny, et al.
Published: (2025)

Mell: Memory-Efficient Large Language Model Serving via Multi-GPU KV Cache Management
by: Qianli, Liu, et al.
Published: (2025)

An Efficient Heterogeneous Co-Design for Fine-Tuning on a Single GPU
by: Yang, Ruijia, et al.
Published: (2026)

WarmServe: Enabling One-for-Many GPU Prewarming for Multi-LLM Serving
by: Lou, Chiheng, et al.
Published: (2025)

Serving Compound Inference Systems on Datacenter GPUs
by: Devata, Sriram, et al.
Published: (2026)

HAS-GPU: Efficient Hybrid Auto-scaling with Fine-grained GPU Allocation for SLO-aware Serverless Inferences
by: Gu, Jianfeng, et al.
Published: (2025)

A Framework for Fine-Grained Synchronization of Dependent GPU Kernels
by: Jangda, Abhinav, et al.
Published: (2023)

Host-Side Telemetry for Performance Diagnosis in Cloud and HPC GPU Infrastructure
by: Darzi, Erfan, et al.
Published: (2025)

A Multi-Objective Framework for Optimizing GPU-Enabled VM Placement in Cloud Data Centers with Multi-Instance GPU Technology
by: Siavashi, Ahmad, et al.
Published: (2025)

FASER: Fine-Grained Phase Management for Speculative Decoding in Dynamic LLM Serving
by: Chen, Wenyan, et al.
Published: (2026)

Unlock the Potential of Fine-grained LLM Serving via Dynamic Module Scaling
by: Wu, Jingfeng, et al.
Published: (2025)

Optimizing Long-context LLM Serving via Fine-grained Sequence Parallelism
by: Li, Cong, et al.
Published: (2025)

PICE: A Semantic-Driven Progressive Inference System for LLM Serving in Cloud-Edge Networks
by: Zhan, Huiyou, et al.
Published: (2025)

Kairos: Low-latency Multi-Agent Serving with Shared LLMs and Excessive Loads in the Public Cloud
by: Chen, Jinyuan, et al.
Published: (2025)

Taming GPU Underutilization via Static Partitioning and Fine-grained CPU Offloading
by: Schieffer, Gabin, et al.
Published: (2026)

Autonomic Cloud Computing: Research Perspective
by: Gill, Sukhpal Singh
Published: (2015)

SkyServe: Serving AI Models across Regions and Clouds with Spot Instances
by: Mao, Ziming, et al.
Published: (2024)

Adaptive, Efficient and Fair Resource Allocation in Cloud Datacenters leveraging Weighted A3C Deep Reinforcement Learning
by: Kumari, Suchi, et al.
Published: (2025)

DeepServe: Serverless Large Language Model Serving at Scale
by: Hu, Junhao, et al.
Published: (2025)

EdgeServing: Deadline-Aware Multi-DNN Serving at the Edge
by: Cao, Jiahe, et al.
Published: (2026)

Nexus:Proactive Intra-GPU Disaggregation of Prefill and Decode in LLM Serving
by: Shi, Xiaoxiang, et al.
Published: (2025)