Cloud Manager CPU Allocation via Hardware Multithreading Parameters
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current cloud management systems inefficiently utilize CPU resources when provisioning virtual machines due to the lack of consideration for hardware multithreading and split core processors, leading to underutilization of processing resources.
Innovation Solution
A cloud manager that monitors and accounts for hardware threads and split core settings, using a hardware multithreading parameter to select and deploy virtual CPUs on host computer systems, allowing for allocation to multiple hardware threads within a physical core instead of just physical cores or single hardware threads.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If virtual CPUs are allocated to hardware threads without regard to physical cores whenhyperthreading is enabled, then the number of available virtual CPUs increases, but CPU resource utilization becomes inefficient
Solution Approach 1:
The patent applies local quality by differentiating the allocation strategy based on the physical core structure. Virtual CPUs are allocated to hardware threads with awareness of their physical core affiliation, allowing different allocation behaviors for threads on the same core versus threads on different cores. This resolves the contradiction by making the allocation quality heterogeneous rather than uniform, improving efficiency while maintaining quantity.
Solution Approach 2:
The patent introduces a new dimension to CPU allocation by considering the physical core hierarchy in addition to hardware threads. Instead of allocating solely at the thread level, the system now operates at two levels: hardware thread level for granularity and physical core level for efficiency constraints. This dimensional addition resolves the contradiction by providing both fine-grained allocation capability and efficiency awareness.
2Device complexity
If only physical processor cores are considered whenhyperthreading is not enabled, then allocation simplicity is maintained, but processing resource utilization becomes inefficient on modern multi-threaded processors
Solution Approach 1:
The patent applies dynamics by making the allocation strategy adaptive to thehyperthreading state and physical core configuration. The system dynamically adjusts between two modes: whenhyperthreading is enabled, it allocates to hardware threads with core awareness; when disabled, it allocates to physical cores. This dynamic adaptation resolves the contradiction by allowing the system to optimize for either simplicity or efficiency based on the operational context.
3Adaptability or versatility
If split core processors are not treated differently in cloud management, then general compatibility is maintained, but the advantages of split core architecture cannot be realized
Solution Approach 1:
The patent applies parameter changes by introducing new parameters to the cloud management system: split core enablement status and subcore configuration details. These parameters allow the system to differentiate between standard and split core processors, enabling specialized allocation strategies that exploit the split core architecture's advantages while maintaining backward compatibility with traditional processors through default behavior.
Data Source
AI summary
A cloud manager monitors available resources on host computer systems, including a number of hardware threads supported by CPUs on the host computer systems and whether or not the CPUs have split core enabled. The cloud manager receives a request to provision a virtual machine (VM) that includes a hardware multithreading parameter that specifies whether hardware multithreading is allowed on the host computer system. The cloud manager then selects a host computer system for the VM taking into consideration the hardware multithreading parameter, the hardware threads supported by the CPU, and the split core settings. The VM is then placed on the selected host computer system using the hardware multithreading parameter. The result is more efficient utilization of CPU resources in a host for a virtual machine.