Nvidia corporation (20240231830). WORKLOAD ASSIGNMENT TECHNIQUE simplified abstract
Contents
- 1 WORKLOAD ASSIGNMENT TECHNIQUE
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 WORKLOAD ASSIGNMENT TECHNIQUE - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Commercial Applications
- 1.9 Questions about Parallel Computing
- 1.10 Original Abstract Submitted
WORKLOAD ASSIGNMENT TECHNIQUE
Organization Name
Inventor(s)
Federico Busato of Santa Clara CA (US)
WORKLOAD ASSIGNMENT TECHNIQUE - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240231830 titled 'WORKLOAD ASSIGNMENT TECHNIQUE
Simplified Explanation
The patent application describes apparatuses, systems, and techniques for distributing workloads in parallel computing. Threads of a group are assigned equal numbers of items based on the locations of non-zero values in a data structure that contains mostly zeros.
- The innovation involves distributing workloads in parallel computing based on the locations of non-zero values in a data structure.
- Threads of a group are assigned equal numbers of items to optimize workload distribution.
- The technique aims to improve efficiency and performance in parallel computing environments.
- By utilizing the data structure effectively, the workload distribution process is streamlined.
- This innovation can enhance the overall scalability and speed of parallel computing systems.
Potential Applications
This technology can be applied in various fields such as:
- High-performance computing
- Data analytics
- Machine learning
- Scientific simulations
- Cloud computing
Problems Solved
The technology addresses the following issues:
- Uneven workload distribution in parallel computing
- Inefficient allocation of resources
- Slow performance due to poor workload management
Benefits
The benefits of this technology include:
- Improved efficiency in parallel computing
- Enhanced performance and speed
- Optimal resource utilization
- Scalability for handling large workloads
Commercial Applications
- This technology can be utilized by companies offering cloud computing services to optimize workload distribution and improve overall performance.
- High-performance computing centers can benefit from this innovation to enhance the speed and efficiency of their operations.
Questions about Parallel Computing
How does workload distribution impact the performance of parallel computing systems?
Workload distribution plays a crucial role in determining the efficiency and speed of parallel computing systems. Uneven distribution can lead to bottlenecks and slower processing times.
What are the key factors to consider when optimizing workload distribution in parallel computing?
Key factors include the number of threads, the nature of the workload, the available resources, and the architecture of the parallel computing system. Optimal distribution ensures balanced utilization of resources and improved performance.
Original Abstract Submitted
apparatuses, systems, and techniques to distribute workloads in parallel computing. in at least one embodiment, threads of a group are assigned equal numbers of items based, at least in part, on locations of non-zero values in a data structure that contains mostly zeros.
