CPU Optimization in Linux for Ultra-Low Latency Trading

In my previous article, I wrote about Network Optimization using Solarflare NICs for ultra-low latency trading. In high-frequency trading (HFT), where each microsecond could make or break a trade, optimizing the performance of not just your network but also your CPU is crucial. CPU optimizations, CPU pinning, RT Scheduling, NUMA, can significantly reduce latency, allowing for faster execution times and better trading performance. In this article, I’ll share insights on CPU optimizations in Linux that are key to achieving ultra-low latency in trading environments.

The Importance of CPU Optimization in HFT

In HFT, processing speed is everything. Your CPU needs to be tuned to minimize delays in handling incoming network data, executing trading algorithms, and sending orders to the market. While network optimizations (such as Solarflare NICs and OpenOnload) are crucial, they must be paired with CPU-level optimizations for maximum impact.

CPU Pinning: Maximizing Performance by Allocating CPU Cores

One of the most effective ways to reduce latency is through CPU pinning. CPU pinning allows you to assign specific tasks or processes to particular CPU cores, ensuring that critical trading tasks have dedicated resources, reducing context switching and improving determinism.

Key Benefits of CPU Pinning:

- Reduced Context Switching: By binding processes to specific CPU cores, you minimize context switching overhead, allowing processes to run uninterrupted.

- Improved Cache Utilization: Pinning processes to cores ensures that the CPU cache is effectively used for that process, reducing the time spent retrieving data from main memory.

- Increased Predictability: Pinning key processes to specific cores ensures that latency is more predictable, which is crucial in trading systems.

We can use tools like taskset or numactl to pin processes to specific CPU cores. For example:

Kernel Bypass for Optimized CPU Usage

Kernel bypass technologies, such as Solarflare’s OpenOnload, allow you to offload packet processing from the kernel to user space, reducing overhead and freeing up CPU cycles for critical tasks. Here's why Kernel Bypass Matters.

- Eliminates Kernel Processing Overhead: By allowing applications to directly communicate with the NIC, you bypass the Linux kernel's networking stack, which typically involves multiple layers of processing.

- Reduces CPU Load: Kernel bypass frees up CPU resources that would otherwise be spent processing system calls and interrupts, allowing more CPU power to be directed toward trading algorithms.

Real-Time Scheduling for Critical Tasks

In addition to CPU pinning, another key optimization is the use of real-time scheduling for critical trading processes. Real-time scheduling ensures that high-priority tasks are executed promptly, without being preempted by lower-priority processes. We can assign a real-time scheduling policy to your process using chrt.

Disabling CPU Power Management for Ultra-Low Latency

In ultra-low latency trading, even minor fluctuations in CPU performance can have a noticeable impact. CPU power-saving features, like C-states and P-states, can introduce variability in response times as CPUs cycle between different power states.

To maintain consistent performance, it's best to disable power-saving features. This ensures that the CPU runs at maximum frequency without throttling, reducing jitter and ensuring the fastest possible response times.

NUMA Optimization: Handling Memory in Multi-Processor Systems

In multi-processor or multi-core systems, Non-Uniform Memory Access (NUMA) can affect performance, as memory access times vary depending on the proximity of the memory to the CPU core accessing it. Key NUMA Optimization Techniques are:

- Process Affinity: Bind both the process and its memory to the same NUMA node to reduce latency.

- Interleaving Memory Access: Ensure that memory is evenly distributed across NUMA nodes for processes that are spread across multiple cores. We can control NUMA behavior using numactl.

I'll discuss more about NUMA in my next article.

Hyper-Threading: To Use or Not to Use?

Hyper-threading can be a double-edged sword in low-latency environments. While it can increase throughput in general-purpose applications, it can introduce jitter in latency-sensitive systems by overloading shared CPU resources (e.g., cache, execution units).

For ultra-low latency trading systems, it is often recommended to disable hyper-threading. This ensures that each core operates independently, minimizing resource contention and reducing variability in execution times.

Wrapping Up

When optimizing a trading system for ultra-low latency, network optimization alone isn’t enough. CPU-level tuning is just as critical. By implementing techniques like CPU pinning, kernel bypassing, and disabling power-saving features, you can drastically improve your system’s responsiveness. Combining these CPU optimizations with fine-tuned NIC configurations like Solarflare’s OpenOnload can help you achieve the microsecond-level performance that’s essential for high-frequency trading.

In the next article, I’ll dive deeper into how you can combine these CPU optimizations with memory configurations to further reduce latency and enhance your trading infrastructure.