dag-scheduling

可视化任务调度系统，精简到一个二进制文件 (Web visual task scheduler system , yes ! just one binary solve all the problems !)

FaaSFlow: Enable Efficient Workflow Execution for Function-as-a-Service

Event-driven simulator for preemptive scheduling of periodic DAG tasks on multi-core edge platforms: EDF across graphs, modified-HEFT upward rank within a graph, and the Priority Ceiling Protocol on shared resources.

HEFT, randomHEFT and IPEFT algorithms for static list DAG Scheduling

A lightweight framework that enables serverless users to reduce their bills by harvesting non-serverless compute resources such as their VMs, on-premise servers, or personal computers.

A kubernetes native workflow orchestrator used to create DAGs that can run on a schedule as well as in an event driven manner

Simple template DAG scheduler in c++

Distributed dependency-aware DAG task offloading and service caching in cloudlet edge computing (distributed DQN + guided action shaping + EMA caching). IEEE TSC 2026.

Acyclic instruction list scheduler ordering basic block dependence graphs by critical path latency to eliminate pipeline stalls.

Acyclic instruction list scheduler ordering basic block dependence graphs by critical path latency to eliminate pipeline stalls.

This Airflow DAG automates the process of extracting data from an Amazon Redshift database and unloading it to Amazon S3 in Parquet format. It runs daily, exporting data from the previous day based on a specified query.

Cache-aware DAG scheduling and memory optimization for SIMD/NPU compute graphs, motivated by LLM inference runtime and compiler problems.

This project implements a full-stack data engineering solution that connects to the Spotify Web API to extract a user’s recently played tracks, stores the data in a PostgreSQL database, applies transformations using dbt, and delivers actionable insights via Metabase dashboards.

🥈 2nd place (Agent-only) MLSys 2026 Track B — Multi-Agent LLM Pipeline for Memory-Constrained Tensor DAG Scheduling. Neurosymbolic split: LLM for combinatorial structure (op fusion), deterministic solver for constraints ([w,h,k], dependency, latency). 7.77× aggregate speedup, 88× best case.

Kernel Memory Manager: Parallel dataflow scheduling and efficient memory management for multi-GPU platforms

Schedule multi-LLM-agent workflows as task graphs across heterogeneous edge, cloud, and API executors. SAGA plans, Wayline executes.

Task-layer speculative execution for coding agents: WorkGraph analysis and an offline reviewer artifact.

GNN quantile runtime prediction and conformal risk calibration for real-time DAG scheduling.

Hard Real-Time Multi-Core DAG Dispatch and Zero-Jitter Avionic Scheduler

A Deterministic Model to Predict Execution Time of Spark Applications (Query-64 of TPC-DS)