ML Inference Scheduling with Predictable Latency #ML #MachineLearning #TaskScheduling hgpu.org/?p=30465

Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters #GPUcluster #TaskScheduling #Package hgpu.org/?p=30451

1% better every day for one year = you become ~37× better. Most people want 100% change overnight and quit by week 2. The **2026 Annual Planner** is built for the 1% life: • Schedule goals on dedicated pages (focus on 3-5 for real progress) • Use weekly spreads to plan tasks and build small daily actions • Finance sheets for tracking monthly revenues and expenses • End with the “Did I Reach My Annual Goals?” reflection to review your scheduled milestones Small, boring, consistent beats big, exciting, sporadic every single time. Want proof? Schedule 4 pages of Qur’an daily in 2026 → you finish it twice. Schedule 10 pages of learning → you read 12 life-changing books. Schedule 1 grateful thing → you end the year with 365 reasons to smile. Start compounding today: amazon.com/dp/B0FTZ9SK9H #CompoundEffect #1PercentBetter #2026Goals #TaskScheduling #SmallWins #MuslimProductivity #QuranGoals

Block: Balancing Load in LLM Serving with Context, Knowledge and Predictive Scheduling #CUDA #LLM #TaskScheduling #Package hgpu.org/?p=30095

🛠️ DevLog – Smarter SLA Node Selection (v1) Further testing led to key improvements in how nodes are matched to SLA tiers. This update addresses an important issue where top-tier nodes (e.g., L6) weren't being properly assigned. 🔹 Dynamic Range Detection - Detects actual min/max node levels in real-time from the pool - Avoids relying on outdated config values 🔹 Top-Down SLA Assignment - Highest SLA tier now guaranteed to include top-level nodes - Lower tiers are derived from remaining levels 🔹 Boundary Protection - Prevents overlapping SLA level ranges - Auto-adjusts boundaries if conflicts arise This ensures that when users request high SLA sessions, the most capable nodes are prioritized - unlocking stronger guarantees for critical workloads. More iterations to come during Phase #5 as we continue evolving toward adaptive task scheduling. #Cortensor #DePIN #AI #TaskScheduling

Specx: a C task-based runtime system for heterogeneous distributed architectures #CUDA #HIP #TaskScheduling #Package hgpu.org/?p=30051

🛠️ DevLog – CognitiveLevel Iteration Begins on DevNet6 The CognitiveLevel module is now deployed to DevNet6, and we're kicking off real iteration. 🔹 Why It Matters Designed to classify nodes based on performance (success streaks, token output, reliability), CognitiveLevel enables smarter, level-aware task routing across the network. 🔹 Current Status - Initial contract deployed - Integration hooks are in place between miners, oracles, and Cognitive - Testing flow: miner → oracle → CognitiveLevel → dynamic prompt selection 🔹 Next Steps - Unit tests and integration testing across full pipeline - Expand oracle tracking for per-task token metrics - Begin miner-side prompt logic tied to node level 🔹 Looking Ahead This will be a multi-phase iteration cycle, requiring extensive testing across all existing network task prompts. Each prompt must be validated to ensure proper behavior under different CognitiveLevel tiers. It's a deep refactor but one that unlocks adaptive routing, tiered incentives, and more precise decentralized execution. #Cortensor #DevLog #CognitiveLevel #DevNet6 #AIInfra #DePIN #PoUW #TaskScheduling

Was reading through your docs the other day to learn more about them. Since I do so much with @DidactPlatform (first version closing in, yay!) I was reading your docs about TaskScheduling. Was really cool reading about the Actor scheduler and how that was wired up in the source code. I saw you have a Quartz dotnet integration for Akka, would love to sync up with you sometime soon and see if we can build an Akka integration piece using @DidactPlatform .

Big News for ChatGPT Users! You can now schedule tasks with the powerful o3 and o4-mini models! #AI #ChatGPT #TaskScheduling #TechCommunity

Concurrent Scheduling of High-Level Parallel Programs on Multi-GPU Systems #SYCL #TaskScheduling #PerformancePortability #HPC #Package hgpu.org/?p=29823

(10/17) Task Management with SessionQueue ⚙️ SessionQueue distributes tasks to miners based on: 🔸 Random selection for load balancing 🔸 Reputation-based scoring for optimized performance SessionQueue ensures AI tasks are assigned efficiently, minimizing congestion. #AI #DePIN #Cortensor #TaskScheduling

You: What is 10 15 ⠋ Assistant is thinking...2024-12-25 20:36:54,017 - TaskManager - INFO - Decomposing task: What is 10 15 2024-12-25 20:36:54,017 - TaskManager - DEBUG - Calling transform function with messages ⠏ Assistant is thinking...2024-12-25 20:37:22,034 - TaskManager - DEBUG - Received decomposition: subtasks=[Subtask(id='1', description='Parse the mathematical expression', tools=[AgentDefinedTool(name='expression parser', description='Parses a mathematical expression into its components', parameters={'expression': '10 15'}, required_permissions=[])], relevancy_criteria=[TaskRelevancyCriteria(priority=1, dependencies=[], conditions=[], prompt_relevancy=1.0, completion_status=0.0, coherence_score=1.0, factual_accuracy=1.0, custom_validation=None)], created_at=1703534400.0, updated_at=1703534400.0, status='pending', scheduling=TaskScheduling(dependencies_status={}, required_resources=['CPU'], deadline=None, max_retries=3, interruptible=True), retry_count=0, checkpoint_data=None), Subtask(id='2', description='Calculate the result of the parsed expression', tools=[AgentDefinedTool(name='calculator', description='Performs calculations', parameters={'operation': 'add', 'operands': ['10', '15']}, required_permissions=[])], relevancy_criteria=[TaskRelevancyCriteria(priority=1, dependencies=['1'], conditions=[], prompt_relevancy=1.0, completion_status=0.0, coherence_score=1.0, factual_accuracy=1.0, custom_validation=None)], created_at=1703534400.0, updated_at=1703534400.0, status='pending', scheduling=TaskScheduling(dependencies_status={'1': <TaskStatus.COMPLETED: 'completed'>}, required_resources=['CPU'], deadline=None, max_retries=3, interruptible=True), retry_count=0, checkpoint_data=None), Subtask(id='3', description='Format the result for output', tools=[AgentDefinedTool(name='formatter', description='Formats the result of a calculation', parameters={'format': 'plain_text', 'value': '25'}, required_permissions=[])], relevancy_criteria=[TaskRelevancyCriteria(priority=1, dependencies=['2'], conditions=[], prompt_relevancy=1.0, completion_status=0.0, coherence_score=1.0, factual_accuracy=1.0, custom_validation=None)], created_at=1703534400.0, updated_at=1703534400.0, status='pending', scheduling=TaskScheduling(dependencies_status={'2': <TaskStatus.COMPLETED: 'completed'>}, required_resources=['CPU'], deadline=None, max_retries=3, interruptible=True), retry_count=0, checkpoint_data=None)] overall_completion_score=0.0 overall_relevancy_score=1.0

Efficient Configuration of Heterogeneous Resources and Task Scheduling Strategies in Deep Learning Auto-Tuning Systems #TaskScheduling #DeepLearning #DL #AI hgpu.org/?p=29465

Hi Devs! ⏰ Learn how to set up task scheduling in Laravel using Cron Jobs. 🛠️ I'll show you an easy step-by-step guide to automate tasks in your Laravel app. Watch the full tutorial! 🎥👇 youtube.com/watch?v=HLelKam4… #Laravel #CronJob #TaskScheduling #PHP #WebDevelopment

6/ Luckily, there's a tool available to handle these problems! By using more advanced schedulers like Airflow or NiFi, you can overcome CronTab's limitations and avoid pipeline breakdowns due to timing issues.#Airflow #TaskScheduling

Today at 6:30 pm we start our 117th @warsawjs #Meetup! Robert Ptasiński: Deep Dive into #JS #taskscheduling @piotr_slawinski: The Dark Forest Of The #DeadInternet Jerzy Nowiński: How to build real-time video processing #webapp Last tickets available app.easycart.pl/checkout/war…

Scheduling Deep Learning Jobs in Multi-Tenant GPU Clusters via Wise Resource Sharing #CUDA #MPI #GPUcluster #TaskScheduling #DeepLearning #DL #PyTorch hgpu.org/?p=29319

Schedule your day with a clear to-do list. Break tasks into smaller steps and tick them off one by one. It’s satisfying and effective! ✍️ #ToDoList #TaskScheduling #AchieveGoals

Do you want to know more about the Ortus Solutions, Corp sessions at #CFCamp and our representatives? Don't miss out - see you there! Register now and secure your spot at #CFCamp Munich: ortussolutions.com/.../ortus…... #CFCAMP #coldfusion #ortussolutions #boxlang #keynotespeaker #developerconference #munich #multiruntime #TaskScheduling #CFML #coldboxdebugger #coding #development #networking

@ortussolutions Soars Back to @cf_camp Munich as Platinum Sponsor and Keynote Presenter! We're thrilled to announce that @ortussolutions is returning to @cf_camp Munich for another year! We're incredibly proud to be a continuing sponsor of this fantastic event and can't wait to connect with the #coldfusion community once again. -Taking Center Stage with the Day 1 Keynote -Unveiling the Power of Ortus Solutions: ---@TryBoxLang : Getting Started and Usage Overview by @bdw429s ---Revolutionizing Task Scheduling in #CFML! By @lmajano ---CBDebugger: Debug your Box apps with ease! By @lmajano Don't miss this incredible opportunity to learn, network, and experience the best of @ortussolutions and @TryBoxLang ! Join us at the Munich Airport Marriott Hotel on June 13th and 14th, 2024. Register now and secure your spot at cfcamp Munich: ortussolutions.com/.../ortus…... #CFCAMP #coldfusion #ortussolutions #boxlang #keynotespeaker #developerconference #munich #multiruntime #TaskScheduling #CFML #coldboxdebugger #coding #development #Networking