8 papers
GraphMend: Code Transformations for Fixing Graph Breaks in PyTorch 2
Savini Kashmira, Jayanaka Dantanarayana, Thamirawaran Sathiyalogeswaran +3
This paper presents GraphMend, a compiler technique that automatically fixes FX graph breaks in PyTorch 2 programs. Although PyTorch 2 introduced TorchDynamo and TorchInductor to e…
Agentic AI Workload Characteristics
Yichao Yuan, Ankita Nayak, Souvik Kundu +1
Agentic AI shifts LLM serving from isolated prompt-generation requests to stateful, multi-turn executions that repeatedly invoke the model, call tools, and grow context over time.…
KAIROS: Stateful, Context-Aware Power-Efficient Agentic Inference Serving
Yichao Yuan, Mosharaf Chowdhury, Nishil Talati
Power has become a central bottleneck for AI inference. This problem is becoming more urgent as agentic AI emerges as a major workload class, yet prior power-management techniques…
BlazingAML: High-Throughput Anti-Money Laundering (AML) via Multi-Stage Graph Mining
Haojie Ye, Arjun Laxman, Yichao Yuan +2
Money laundering detection faces challenges due to excessive false positives and inadequate adaptation to sophisticated multi-stage schemes that exploit modern financial networks.…
ZKProphet: Understanding Performance of Zero-Knowledge Proofs on GPUs
Tarunesh Verma, Yichao Yuan, Nishil Talati +1
Zero-Knowledge Proofs (ZKP) are protocols which construct cryptographic proofs to demonstrate knowledge of a secret input in a computation without revealing any information about t…
MoDM: Efficient Serving for Image Generation via Mixture-of-Diffusion Models
Yuchen Xia, Divyam Sharma, Yichao Yuan +2
Diffusion-based text-to-image generation models trade latency for quality: small models are fast but generate lower-quality images, while large models produce better images but are…