What is NUMA in Hyper-V?
NUMA stands for Non-Uniform Memory Access, and it’s a memory design feature found in multi-processor systems. It becomes especially important when you’re working with virtual machines in Hyper-V, Microsoft's virtualization platform. To understand NUMA in this context, you first have to understand how memory is handled in server-grade hardware. In traditional systems, all processors share a single memory pool. But in more advanced systems with multiple processors, memory access speeds can vary depending on where the processor is located in relation to the memory. This is where NUMA fits in.
In a NUMA system, each processor (or group of processors) has its own local memory. However, these processors can also access memory that’s physically attached to other processors, but the access time will be longer. This is why it's called "non-uniform" memory access—it’s not the same speed across the system. When you’re running virtual machines, understanding how NUMA impacts performance can be critical.
NUMA and Hyper-V's Virtual Machines
When you create and run virtual machines on Hyper-V, they are essentially designed to use the underlying physical hardware resources. So, Hyper-V must consider the underlying NUMA architecture when allocating virtual CPUs and memory. If Hyper-V isn’t properly aware of NUMA, it could place virtual machines in ways that degrade performance due to inefficient memory access patterns. NUMA helps to optimize the performance of these virtual machines by ensuring that each virtual processor (vCPU) is paired with memory that is local to the physical CPU it runs on.
The relationship between virtual processors and physical memory becomes key here. Let’s say you’ve got a multi-socket system. In this system, each socket has its own memory region. If Hyper-V doesn’t respect NUMA boundaries, a virtual machine might have its vCPU running on one processor while accessing memory from a completely different processor’s local memory. This means it might need to go across the system to access the data, causing slower performance. Hyper-V tries to be NUMA-aware, but you need to make sure the system is configured correctly to maximize the benefits.
How Hyper-V Configures NUMA for Virtual Machines
Hyper-V typically tries to make sure virtual machines are scheduled in a way that aligns with the physical NUMA nodes. Each NUMA node consists of a CPU (or set of CPUs) and its associated memory. When you create a VM, Hyper-V attempts to ensure that the virtual CPUs and memory are allocated in the most efficient way possible, based on the NUMA layout of the host machine.
When you look at the hardware configuration of your VM, Hyper-V has a feature where it maps the vCPUs to physical processors and memory in a way that makes the most sense given the NUMA layout. If your physical server has multiple NUMA nodes, Hyper-V will try to place the VM’s virtual processors on the same NUMA node as the memory it’s using. This reduces latency and helps ensure that the virtual machine performs optimally. However, this is not always perfect. Sometimes, depending on the configuration of the host machine or the way the virtual machine is created, NUMA configurations can be misaligned, causing suboptimal performance.
One key thing to keep in mind is that Hyper-V doesn’t just passively let the hardware handle NUMA. It gives you tools to configure and monitor NUMA alignment. If you have specific performance requirements for a virtual machine, you can adjust settings to ensure that NUMA is respected correctly. For instance, you can manually assign more than one NUMA node to a virtual machine if you want to spread its resources more evenly, but this can be tricky if not done carefully.
NUMA Aware vs. NUMA Unaware VMs
The concept of NUMA-aware and NUMA-unaware virtual machines is pretty important when talking about NUMA and Hyper-V. If a virtual machine is NUMA-aware, it knows about the NUMA topology of the underlying hardware. It can make intelligent decisions on where to place its virtual CPUs and how to access memory efficiently. Most modern applications and operating systems are NUMA-aware, and Hyper-V will work with these to make sure the VMs are running as efficiently as possible.
On the other hand, if a virtual machine is NUMA-unaware, it doesn’t have any knowledge of the physical NUMA topology. It will treat memory and processor access as if it were a traditional, uniform system. In this case, Hyper-V has to work harder to make sure the VM’s virtual CPUs and memory are allocated properly. It may not always be able to optimize things as well, potentially leading to performance issues.
If you’ve got applications running inside your VM that are NUMA-unaware, you might see performance slowdowns, especially when the VM is spread across multiple NUMA nodes. This is another reason why it’s so important to ensure that your virtual machine’s NUMA configuration is set up properly and that the workloads running on it are NUMA-aware when possible.
NUMA Balancing in Hyper-V
Hyper-V has a feature called NUMA balancing, which automatically adjusts the placement of virtual CPUs and memory within the NUMA nodes based on the current workload. When a virtual machine is running, the memory demand might change. NUMA balancing ensures that as the workload grows, the VM's memory and virtual CPUs stay as close as possible to each other in the physical hardware. This dynamic balancing helps prevent situations where memory and CPUs are too far apart, which would increase latency and hurt performance.
What makes NUMA balancing interesting is that it’s not static. It reacts to the system’s state, shifting resources dynamically as needed. For instance, if one NUMA node is getting too busy, Hyper-V may decide to move some virtual processors to a less loaded NUMA node to balance the load more evenly. This can help avoid performance degradation when the system is under heavy load.
The key benefit of NUMA balancing is that it helps ensure your virtual machines keep running at optimal performance without manual intervention. Of course, if you need more granular control, you can disable NUMA balancing or manually configure NUMA settings, but most of the time, letting Hyper-V handle it automatically is your best bet.
Troubleshooting NUMA Issues in Hyper-V
If you’re experiencing performance problems in a Hyper-V environment and suspect NUMA might be a factor, there are a few things to check. First, make sure your virtual machines are properly aligned with the NUMA nodes. You can use PowerShell or the Hyper-V Manager to check the NUMA configuration of a VM. This will tell you how many NUMA nodes the VM is using and whether they are aligned correctly.
If a VM is spanning multiple NUMA nodes, it’s important to figure out whether this is intentional or if it’s causing performance issues. A good rule of thumb is to try to avoid assigning a VM to more NUMA nodes than it needs. If the VM is already spread across multiple NUMA nodes, consider reducing the number of virtual CPUs or adjusting the memory allocation to make the NUMA layout more efficient.
Sometimes, issues can arise from the host system itself. If the physical server is misconfigured or running too many VMs, this can cause NUMA-related problems. In these cases, you may need to adjust the overall system configuration, either by upgrading hardware or optimizing the number of VMs running on the server.
Hyper-V also provides diagnostic tools to help you pinpoint where the NUMA issues are coming from. One such tool is the Performance Monitor, which you can use to track CPU and memory usage across NUMA nodes. If you notice that one NUMA node is getting overloaded while others are underused, this could be a sign that your VM’s NUMA configuration is off.
If all else fails, reviewing the logs and performance counters can help identify if NUMA imbalance is causing the slowdowns. Keeping an eye on your Hyper-V setup, and making sure NUMA is properly configured, can help prevent most issues before they impact performance.
I hope my post was useful. Are you new to Hyper-V and do you have a good Hyper-V backup solution? See my other post
NUMA stands for Non-Uniform Memory Access, and it’s a memory design feature found in multi-processor systems. It becomes especially important when you’re working with virtual machines in Hyper-V, Microsoft's virtualization platform. To understand NUMA in this context, you first have to understand how memory is handled in server-grade hardware. In traditional systems, all processors share a single memory pool. But in more advanced systems with multiple processors, memory access speeds can vary depending on where the processor is located in relation to the memory. This is where NUMA fits in.
In a NUMA system, each processor (or group of processors) has its own local memory. However, these processors can also access memory that’s physically attached to other processors, but the access time will be longer. This is why it's called "non-uniform" memory access—it’s not the same speed across the system. When you’re running virtual machines, understanding how NUMA impacts performance can be critical.
NUMA and Hyper-V's Virtual Machines
When you create and run virtual machines on Hyper-V, they are essentially designed to use the underlying physical hardware resources. So, Hyper-V must consider the underlying NUMA architecture when allocating virtual CPUs and memory. If Hyper-V isn’t properly aware of NUMA, it could place virtual machines in ways that degrade performance due to inefficient memory access patterns. NUMA helps to optimize the performance of these virtual machines by ensuring that each virtual processor (vCPU) is paired with memory that is local to the physical CPU it runs on.
The relationship between virtual processors and physical memory becomes key here. Let’s say you’ve got a multi-socket system. In this system, each socket has its own memory region. If Hyper-V doesn’t respect NUMA boundaries, a virtual machine might have its vCPU running on one processor while accessing memory from a completely different processor’s local memory. This means it might need to go across the system to access the data, causing slower performance. Hyper-V tries to be NUMA-aware, but you need to make sure the system is configured correctly to maximize the benefits.
How Hyper-V Configures NUMA for Virtual Machines
Hyper-V typically tries to make sure virtual machines are scheduled in a way that aligns with the physical NUMA nodes. Each NUMA node consists of a CPU (or set of CPUs) and its associated memory. When you create a VM, Hyper-V attempts to ensure that the virtual CPUs and memory are allocated in the most efficient way possible, based on the NUMA layout of the host machine.
When you look at the hardware configuration of your VM, Hyper-V has a feature where it maps the vCPUs to physical processors and memory in a way that makes the most sense given the NUMA layout. If your physical server has multiple NUMA nodes, Hyper-V will try to place the VM’s virtual processors on the same NUMA node as the memory it’s using. This reduces latency and helps ensure that the virtual machine performs optimally. However, this is not always perfect. Sometimes, depending on the configuration of the host machine or the way the virtual machine is created, NUMA configurations can be misaligned, causing suboptimal performance.
One key thing to keep in mind is that Hyper-V doesn’t just passively let the hardware handle NUMA. It gives you tools to configure and monitor NUMA alignment. If you have specific performance requirements for a virtual machine, you can adjust settings to ensure that NUMA is respected correctly. For instance, you can manually assign more than one NUMA node to a virtual machine if you want to spread its resources more evenly, but this can be tricky if not done carefully.
NUMA Aware vs. NUMA Unaware VMs
The concept of NUMA-aware and NUMA-unaware virtual machines is pretty important when talking about NUMA and Hyper-V. If a virtual machine is NUMA-aware, it knows about the NUMA topology of the underlying hardware. It can make intelligent decisions on where to place its virtual CPUs and how to access memory efficiently. Most modern applications and operating systems are NUMA-aware, and Hyper-V will work with these to make sure the VMs are running as efficiently as possible.
On the other hand, if a virtual machine is NUMA-unaware, it doesn’t have any knowledge of the physical NUMA topology. It will treat memory and processor access as if it were a traditional, uniform system. In this case, Hyper-V has to work harder to make sure the VM’s virtual CPUs and memory are allocated properly. It may not always be able to optimize things as well, potentially leading to performance issues.
If you’ve got applications running inside your VM that are NUMA-unaware, you might see performance slowdowns, especially when the VM is spread across multiple NUMA nodes. This is another reason why it’s so important to ensure that your virtual machine’s NUMA configuration is set up properly and that the workloads running on it are NUMA-aware when possible.
NUMA Balancing in Hyper-V
Hyper-V has a feature called NUMA balancing, which automatically adjusts the placement of virtual CPUs and memory within the NUMA nodes based on the current workload. When a virtual machine is running, the memory demand might change. NUMA balancing ensures that as the workload grows, the VM's memory and virtual CPUs stay as close as possible to each other in the physical hardware. This dynamic balancing helps prevent situations where memory and CPUs are too far apart, which would increase latency and hurt performance.
What makes NUMA balancing interesting is that it’s not static. It reacts to the system’s state, shifting resources dynamically as needed. For instance, if one NUMA node is getting too busy, Hyper-V may decide to move some virtual processors to a less loaded NUMA node to balance the load more evenly. This can help avoid performance degradation when the system is under heavy load.
The key benefit of NUMA balancing is that it helps ensure your virtual machines keep running at optimal performance without manual intervention. Of course, if you need more granular control, you can disable NUMA balancing or manually configure NUMA settings, but most of the time, letting Hyper-V handle it automatically is your best bet.
Troubleshooting NUMA Issues in Hyper-V
If you’re experiencing performance problems in a Hyper-V environment and suspect NUMA might be a factor, there are a few things to check. First, make sure your virtual machines are properly aligned with the NUMA nodes. You can use PowerShell or the Hyper-V Manager to check the NUMA configuration of a VM. This will tell you how many NUMA nodes the VM is using and whether they are aligned correctly.
If a VM is spanning multiple NUMA nodes, it’s important to figure out whether this is intentional or if it’s causing performance issues. A good rule of thumb is to try to avoid assigning a VM to more NUMA nodes than it needs. If the VM is already spread across multiple NUMA nodes, consider reducing the number of virtual CPUs or adjusting the memory allocation to make the NUMA layout more efficient.
Sometimes, issues can arise from the host system itself. If the physical server is misconfigured or running too many VMs, this can cause NUMA-related problems. In these cases, you may need to adjust the overall system configuration, either by upgrading hardware or optimizing the number of VMs running on the server.
Hyper-V also provides diagnostic tools to help you pinpoint where the NUMA issues are coming from. One such tool is the Performance Monitor, which you can use to track CPU and memory usage across NUMA nodes. If you notice that one NUMA node is getting overloaded while others are underused, this could be a sign that your VM’s NUMA configuration is off.
If all else fails, reviewing the logs and performance counters can help identify if NUMA imbalance is causing the slowdowns. Keeping an eye on your Hyper-V setup, and making sure NUMA is properly configured, can help prevent most issues before they impact performance.
I hope my post was useful. Are you new to Hyper-V and do you have a good Hyper-V backup solution? See my other post
