SYSTEM AND METHOD FOR INREASING ROBUSTNESS OF HETEROGENEOUS COMPUTING SYSTEMS

Patent №

US 11,455,188

Granted

2022-09-27

Filed 2020

Owner

UNIVERSITY OF LOUISIANA AT LAFAYETTE

Lab

AI components

1

hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

16860286

Disclosed is a method for task pruning that can be utilized in existing resource allocation systems to improve the systems' robustness without requiring changing to existing mapping heuristics. The pruning mechanism leverages a probability model, which calculates the probability of a task competing before its deadline in the presence of task dropping, and only schedules tasks that are likely to succeed. Pruning tasks whose chance of success is low improves the chance of success for other tasks. Tasks that are unlikely to succeed are either deferred from current scheduling event or are preemptively dropped from the system. The pruning method can benefit service providers by allowing them to utilize their resources more efficiently and use them only for tasks that can meet their deadlines. The pruning method further helps end users by making the system more robust in allowing more tasks to complete on time.

AI hardwareG06F 9/4881G06F 9/4887G06F 9/5011G06F 9/5022G06F 9/5038G06F 9/505G06F 9/546G06F 2209/483+3 more

AI classification

AI hardware1.00
Machine learning0.47
Knowledge representation0.01
Planning0.01
Natural language0.00
Speech0.00
Evolutionary computation0.00
Vision0.00

Ownership

UNIVERSITY OF LOUISIANA AT LAFAYETTE

assignment · 532510698

Assignors

JAMES GENTRY, MOHSEN AMINI SALEHI, CHAVIT DENNINNART

On an employer assignment, the assignors are typically the inventors.

© 2026 NYSGPT2525 LLC