Program

All program times are in Central European Summer Time (CEST, UTC+2).

At a Glance

Time Monday
May 4		 Tuesday
May 5		 Wednesday
May 6		 Thursday
May 7		 Friday
May 8
08:00-09:00 Workshops
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Tutorials (TBA)		 Workshops
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Tutorials (TBA)		 Registration
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Conference Opening		 Registration (from 8:30) Registration (from 8:30)
09:00-10:00 Workshops
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Tutorials (TBA)		 Workshops
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Tutorials (TBA)		 Keynote 1
Leana Golubchik		 Keynote 2
Didem Unat		 Keynote 3
Jeff Hammond
10:00-10:30 TBA TBA Session 1 Session 5 Session 9
10:30-11:00 Coffee Break Coffee Break Coffee Break Coffee Break Coffee Break
11:00-12:30 Workshops
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Tutorials (TBA)		 Workshops
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Tutorials (TBA)		 Session 2 Session 6 Session 10
12:30-14:00 Lunch Lunch Lunch / Posters & Demonstrations Lunch / Posters & Demonstrations Lunch / Posters & Demonstrations
14:00-15:30 Workshops
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Tutorials (TBA)		 Workshops
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Tutorials (TBA)		 Session 3 Session 7 Session 11
15:30-16:00 Coffee Break Coffee Break Coffee Break Coffee Break Closing Session
16:00-17:30 Workshops
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Tutorials (TBA)		 Workshops
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Tutorials (TBA)		 Panel + Session 4 Session 8
Evening

Detailed Program

Monday, May 4, 2026

TBA

Tuesday, May 5, 2026

TBA

Wednesday, May 6, 2026

Time Slot Program
08:00-08:45 Registration
08:45-09:00 Conference Opening
09:00-10:00 Keynote 1 Leana Golubchik (University of Southern California) — Systems for AI: Predicting Performance of Machine Learning Workloads
10:00-10:30 Session 1 Energy Efficiency & Simulation Performance

  • 10:00-10:20 Improving Energy Efficiency and Performance of Weather and Climate Simulations by Leveraging the Heterogeneity of Modern Systems (Research Track)
  • 10:20-10:30 Cross-Platform, Cross-Framework Development of Hybrid-Parallel Matrix-Multiplication codes (Short – Research Track)
10:30-11:00 Coffee Break
11:00-12:32 Session 2 Cloud Systems & Resource Efficiency

  • 11:00-11:20 CarbonShare: Carbon-Fair Allocation for Shared Clusters (Research Track)
  • 11:20-11:40 Kill Smart, Run Fast: Using Job Termination for Efficient and Fair Scheduling in Data Centers (Research Track)
  • 11:40-12:00 Understanding Foundational Library Energy Consumption (Research Track)
  • 12:00-12:12 The Impact of Memory Configuration on Server Efficiency (Industry Track)
  • 12:12-12:24 On the Efficiency and Disruption Trade-Offs of Kubernetes Packing Heuristics (Industry Track)
  • 12:24-12:32 Energy- and Quantization-aware DNN Partitioning in the Edge-Cloud Continuum (Emerging Research Track)
12:32-14:00 Lunch / Posters & Demonstrations
14:00-15:32 Session 3 AI & LLM Performance

  • 14:00-14:20 SweetSpot: An Analytical Model for Predicting Energy Efficiency of LLM Inference (Research Track)
  • 14:20-14:40 B-Perf: Black-box Performance Antipattern Detection Using System-level Execution Tracing (Research Track)
  • 14:40-15:00 ORION: Integrated Runtime Modelling for Predicting Deep Learning Training Time (Research Track)
  • 15:00-15:20 SwiftSNNI: Optimized Scheduling for Secure Neural Network Inference (SNNI) on Multi-Core Systems (Research Track)
  • 15:20-15:32 Evaluating Kubernetes Performance for GenAI Inference: From Automatic Speech Recognition to LLM Summarization (Industry Track)
15:32-16:00 Coffee Break
16:00-17:00 Panel Performance engineering in the era of GenAI: what stays, what goes, and what's next
17:00-17:30 Session 4 System Observability & Latency

  • 17:00-17:20 Benchmarking the Overhead of Distributed Tracing Agents (Research Track)
  • 17:20-17:30 Modeling Extreme End-to-End Delays for Availability Assessment on Latency Datasets (Short – Research Track)

Thursday, May 7, 2026

Time Slot Program
08:30-09:00 Registration
09:00-10:00 Keynote 2 Didem Unat (Koç University) — Illuminating Multi-GPU Communication Paths
10:00-10:30 Session 5 Benchmarking & Profiling Infrastructure

  • 10:00-10:20 benchkit: A Declarative Framework for Composable Performance Evaluation of System Software (Research Track)
  • 10:20-10:30 Performance and Cost Implications of Migrating Serverless Functions from x86 to ARM based Servers (Short – Research Track)
10:30-11:00 Coffee Break
11:00-12:30 Session 6 Performance Modeling and Optimization of Complex Systems

  • 11:00-11:20 Variability-Guided Performance Optimization (Research Track - Best Paper candidate)
  • 11:20-11:40 Energy-Efficient Right-Sizing of Kafka-like Message Brokers for IoT Workloads (Research Track - Best Paper candidate)
  • 11:40-12:00 Performance Analysis and Optimization of 3D Generative Diffusion Models across GPU (Research Track - Best Paper candidate)
  • 12:00-12:20 A Comparative Evaluation of Imputation Models for Agricultural Weather Networks (Research Track - Best Paper candidate)
12:30-14:00 Lunch / Posters & Demonstrations
14:00-15:32 Session 7 GPU & Heterogeneous Computing

  • 14:00-14:20 MQGPU: A Multi-Queue Scheduling Framework For GPU Accelerated Serverless Functions (Research Track)
  • 14:20-14:40 LSTC: Large-Scale Triangle Counting on Single GPU (Research Track)
  • 14:40-15:00 Pulse: A Profiling and Visualization Infrastructure for Heterogeneous Managed Systems (Research Track)
  • 15:00-15:12 Low-Latency ML Offloading Across Edge and IoT Devices (Industry Track)
  • 15:12-15:24 A Transparent and Efficient Performance Analysis Approach to Enhance DPDK Observability (Industry Track)
  • 15:24-15:32 A Taxonomy of Application Properties for Mixed-Precision Autotuning (Emerging Research Track)
15:32-16:00 Coffee Break
16:00-17:30 Session 8 Adaptive Cloud & Edge

  • 16:00-16:20 WASL: Harmonizing Uncoordinated Adaptive Modules in Multi-Tenant Cloud Systems (Research Track)
  • 16:20-16:32 KLUE: A Framework for Cost-Effective Experimentation in Emulated Kubernetes Clusters (Industry Track)
  • 16:32-16:42 FLYT: Transparent and Elastic GPU Provisioning for Multi-Tenant Cloud Services (Short – Research Track)
  • 16:42-16:52 To Offload or Not To Offload: Model-driven Comparison of Edge-native and On-device Processing (Short – Research Track)
16:52-17:30 Awards SPEC Research Group presentation;
SPEC Kaivalya Dixit Distinguished Dissertation Award talk;
ICPE MIP Award presentation

Friday, May 8, 2026

Time Slot Program
08:30-09:00 Registration
09:00-10:00 Keynote 3 Jeff Hammond (NVIDIA) — State-of-the-Art Communication Software for Supercomputers and Its Applications
10:00-10:32 Session 9 Java & Heap Performance

  • 10:00-10:20 MapReplay: Trace-Driven Benchmark Generation for Java HashMap (Research Track)
  • 10:20-10:32 G1HeapVis: Visualizing and Measuring Heap Fragmentation (Industry Track)
10:32-11:00 Coffee Break
11:00-12:30 Session 10 Adaptive Systems & Predictive Management

  • 11:00-11:20 Are We There Yet? Predicting if Executing Applications are Near Completion (Research Track)
  • 11:20-11:40 Holpaca: Holistic and Adaptable Cache Management for Shared Environments (Research Track)
  • 11:40-12:00 Energy-efficient Dynamic Partitioning and Tensors Compression of AI Applications in Smart Eyewears (Research Track)
  • 12:00-12:20 An Evaluation Study of Generative AI Systems: Framework-Aware Performance Under Real-World Constraints (Research Track)
  • 12:20-12:30 Trust Your Local Scaler: A Continuous, Decentralized Approach to Autoscaling (Journal First Track)
12:30-14:00 Lunch / Posters & Demonstrations
14:00-15:30 Session 11 Emerging Trends & Data Challenges

  • 14:00-14:08 Leveraging LLMs for Structured Information Extraction and Analysis from Cloud Incident Reports (Emerging Research Track)
  • 14:08-14:16 Detecting Silent Failures in Multi-Agentic AI Trajectories (Emerging Research Track)
  • 14:16-14:24 Unsupervised Cycle Detection in Agentic Applications (Emerging Research Track)
  • 14:24-14:32 An Agent-Based Approach to Automating Software Performance Testing (Emerging Research Track)
  • 14:32-14:40 Representation-Aware RCA with Large Language Models (Emerging Research Track)
  • 14:40-14:48 Platooning Without Leaders: A Performance-Driven Reframing of Cooperative Vehicle Systems (Emerging Research Track)
  • 14:48-14:56 A Bayesian Way of Estimating Method Cost from Conflicting Profiler Data (Emerging Research Track)
  • 14:56-15:04 Beyond Reproduction: Uncovering Latent Performance Regressions with LLM-Guided Fuzzing (Emerging Research Track)
  • 15:04-15:12 Performance Alert Triage with Time-Aware Learning and Multi-Scale Time-Series Features (Data Challenge Track)
  • 15:12-15:20 Performance Regressions Prediction using Time Series Classification: A Case Study (Data Challenge Track)
  • 15:20-15:28 Weekly Seasonality in Cloud Demand: Lessons from Snowflake’s Shaved Ice Dataset (Data Challenge Track)
15:30-16:00 Closing Closing Session