Dynamic CPU Allocation for Ethernet Server Bandwidth Optimization
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Solution Overview
Problem
Traditional hard disk drives limit the efficiency of storage systems, and while InfiniBand standard achieves high access efficiency, it is expensive and not compatible with Ethernet, making it difficult to achieve similar efficiency in Ethernet environments.
Innovation Solution
A method and server configuration that dynamically allocates central processing units by testing server efficiency, increasing the number of processing units based on workload and bandwidth utilization to optimize processing and avoid resource waste, using a combination of hardware and software queues to manage network packets and tasks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If InfiniBand standard is used to achieve high access efficiency, then access speed is improved, but cost increases and Ethernet compatibility is lost
Solution Approach 1:
The patent uses standard Ethernet network cards instead of expensive InfiniBand hardware, accepting that Ethernet has inherent delays but avoiding the high cost and complexity of InfiniBand infrastructure. This principle applies by choosing a cheaper, more versatile networking standard that suffices for the application needs.
Solution Approach 2:
The patent replaces hardware-level optimization (InfiniBand physical layer) with software-level optimization (process allocation algorithms). Instead of relying on specialized hardware to achieve high performance, the system uses intelligent CPU task scheduling and resource allocation to compensate for Ethernet's limitations.
2Productivity
If more central processing units are allocated to perform tasks, then processing capability is improved, but resource waste increases when bandwidth is already sufficient
Solution Approach 1:
The patent implements a feedback mechanism that continuously monitors server efficiency and bandwidth utilization. Based on this feedback, the system dynamically adjusts the number of CPU processes allocated to network tasks, increasing allocation when bandwidth is available and reducing it when bandwidth is sufficient, thus avoiding resource waste.
Solution Approach 2:
The patent makes the CPU allocation dynamic rather than static. The system adapts the number of active processes based on real-time conditions such as server efficiency, bandwidth availability, and task priorities, allowing flexible resource allocation that matches actual demand.
3Productivity
If the number of central processing units is increased to handle high bandwidth, then processing capability is improved, but system complexity increases
Solution Approach 1:
The patent segments CPU tasks into different types (first type tasks for network processing, second type tasks for other operations) and allocates CPU cores accordingly. This segmentation allows the system to handle high bandwidth by dedicating specific CPU resources to network processing without unnecessarily increasing overall system complexity.
Data Source
AI summary
An allocation method for central processing units and a server using the allocation method are provided. The allocation method includes the following steps: testing a first efficacy of a server and recording a first number of first central processing unit(s) configured to perform a first task, a second number of second central processing unit(s) configured to perform a second task and the first efficacy; determining whether the first central processing unit(s) is in a busy state; increasing the first number when the first central processing unit(s) is in the busy state; determining whether a bandwidth occupied by the first task reaches a maximum bandwidth when the first central processing unit(s) is not in the busy state; increasing the second number when the bandwidth occupied by the first task does not reach the maximum bandwidth; continuously performing the aforementioned steps.