Empowering Efficiency: PEAKS - Orchestrating Power-Aware Kubernetes Scheduling
Innovative Kubernetes scheduler optimizing power efficiency through ML-driven node recommendations, reducing energy consumption in cloud-native environments while maintaining performance.
Orca - A Distributed Serving System for Transformer-Based Generative Models
Explore Orca, a distributed serving system for transformer-based generative models, featuring iteration-level scheduling and selective batching to enhance performance and efficiency in large-scale language model inference.
Rammer - Enabling Holistic Deep Learning Compiler Optimizations with rTasks
Optimizing DNN computation on hardware accelerators through novel abstractions and holistic scheduling, achieving significant performance improvements over existing compilers and libraries.
Introduction to C++ Coroutines Through a Thread Scheduling Demonstration
Explore C++20 coroutines for efficient CPU-GPU multitasking, improving performance in heterogeneous workloads. Learn fundamental components and design a lightweight programming model with scheduling algorithm.
Real Time - MC
Explore real-time computing concepts and applications in Linux systems, focusing on mission-critical operations and performance optimization techniques.
Scheduler MC
Explore advanced Linux scheduling concepts and techniques in this comprehensive conference session, focusing on optimizing system performance and resource allocation.
Intro + Deep Dive - Provider IBM Cloud
Overview of IBM Cloud Provider subproject, recent developments, and activities in cloud-native computing, including CCM, ManageIQ, and multi-cluster management.
Building a Custom Kubernetes Scheduler
Learn to build a custom Kubernetes scheduler, exploring advanced container orchestration techniques and enhancing your understanding of Kubernetes internals.
Optimizing Google Search and Beyond with Pluggable Scheduling
Explore advanced techniques for optimizing Google Search through pluggable scheduling, enhancing performance and efficiency in large-scale systems.
Work Assisting - Linking Task-Parallel Work Stealing with Data-Parallel Self Scheduling
Explore a novel scheduling strategy for mixing data and task parallelism, preserving data parallelism structure while enabling flexible thread distribution and self-scheduling for improved performance.
Fairness in Serving Large Language Models
Explore innovative scheduling algorithms for fair and efficient LLM inference services, addressing challenges of unpredictable request lengths and unique batching characteristics on parallel accelerators.
USHER: Holistic Interference Avoidance for Resource Optimized ML Inference
Optimizes ML inference systems by maximizing GPU resource utilization and minimizing interference, resulting in higher goodput and cost-efficiency for deep learning model deployment.
Low Complexity Optimal Policies for Networked Control Systems
Explore optimal scheduling policies for wireless networked control systems, focusing on channel observation, risk-sensitive cost criteria, and half-duplex controller scenarios in communication networks.
Introduction to Real-Time Linux - Unleashing Deterministic Computing
Explore real-time Linux: definition, myths, target markets, kernel preemption, and PREEMPT_RT. Learn about Ubuntu 22.04 LTS Beta's real-time capabilities for deterministic computing.
How to Increase the Throughput of Kubernetes Scheduler by Tens of Times
Explore advanced techniques to significantly boost Kubernetes scheduler performance, including algorithm optimization, parallel computation, and batch scheduling for improved cluster scalability and resource utilization.
WASM and KWOK Wizardry - Writing and Testing Kubernetes Scheduler Plugins at Scale
Discover how to optimize Kubernetes scheduling by building custom plugins with WebAssembly and testing at scale using KWOK, focusing on performance metrics and efficient cluster management.