Search Results for author:
Found 5 papers, 2 papers with code
Optimizing LLM Queries in Relational Workloads
In this paper, we explore how to optimize LLM inference for analytical workloads that invoke LLMs within relational queries.
Context-Aware Streaming Perception in Dynamic Environments
These works evaluate accuracy offline, one image at a time.
Pay Attention to Convolution Filters: Towards Fast and Accurate Fine-Grained Transfer Learning
We propose an efficient transfer learning method for adapting ImageNet pre-trained Convolutional Neural Network (CNN) to fine-grained image classification task.
The OoO VLIW JIT Compiler for GPU Inference
Current trends in Machine Learning~(ML) inference on hardware accelerated devices (e. g., GPUs, TPUs) point to alarmingly low utilization.
InferLine: ML Inference Pipeline Composition Framework
The dominant cost in production machine learning workloads is not training individual models but serving predictions from increasingly complex prediction pipelines spanning multiple models, machine learning frameworks, and parallel hardware accelerators.
Distributed, Parallel, and Cluster Computing
