ACADEMY
MINING EDITION
MODULE 3
LESSON 2
Miner Performance Tuning for Qubic
Mining Qubic effectively requires not just good hardware but also smart tuning. Here we’ll cover how to squeeze the most performance out of your rig through thread optimization, balancing CPU/GPU usage, managing heat, and OS-level tweaks.
Thread Count Optimization
Thread Count Optimization: Unlike some simplistic miners, Qubic’s AI training can exhibit diminishing returns with too many threads or hyperthreading. It’s often not optimal to simply use 100% of your CPU cores with hyperthreading. Each additional thread increases work but also contention for resources like cache and memory bandwidth. Many miners find a sweet spot where using around 70–80% of logical cores yields higher iterations per second than maxing out all cores with Hyper-Threading enabled.
From community and developer experience, the best practice is to leave 1–2 CPU cores unused out of your total count (for example, mining on 30 out of 32 threads). This small reduction lowers CPU temperature and power draw while only decreasing hashrate by less than 1%.
For example, a 16-core / 32-thread CPU might perform best at around 16–24 threads instead of all 32. Experiment with your thread count (CpuThreads setting) to find your ideal balance. Sometimes less is more — especially if running a GPU concurrently. Monitor your miner’s output or pool dashboard to compare solution rates.
CPU vs RAM Balancing
Qubic’s AI tasks are memory-intensive. Fast RAM and sufficient memory are crucial. Ensure you have at least 16 GB of RAM (preferably preferably DDR5 with high frequency and low latency — ideally CL32 or lower) for a multi-threaded setup . If you allocate too many threads without enough RAM, your system may start swapping (which devastates performance). A key tuning here is enabling Huge Pages (large memory pages) on your OS . Huge pages allow the miner to access memory in bigger chunks, reducing overhead. The Qubic trainer will actually warn you if your system isn’t configured with enough large pages and tell you how many to enable . On Linux, this is as simple as running the suggested sysctl -w vm.nr_hugepages=<number> command as root before starting the miner. On Windows, enabling large page support requires granting the “Lock Pages in Memory” privilege to your user – an advanced step that can also improve performance in some cases. By matching huge pages to the miner’s needs, you can gain a noticeable uptick in iterations per second, especially on big multi-core systems.
Heat Management and Cooling
Qubic mining will drive your hardware to 100% utilization for extended periods . This generates significant heat, especially on CPUs with many cores and high TDP. Proper cooling isn’t just about protecting your hardware – an overheated CPU or GPU will throttle down, sharply reducing your mining performance and shortening the life of your CPU. Make sure your rig has adequate airflow; consider aftermarket CPU coolers if using a desktop processor, or ramp up fan curves to keep temperatures in check. Good cooling is essential – for instance, an AMD Ryzen 9 or Threadripper at full tilt can easily hit 90°C+ without proper cooling, which will trigger thermal throttling. Aim to keep CPUs under ~80°C and GPUs under ~70–75°C for sustained operation. If temperatures are still too high, you can slightly underclock or undervolt your CPU to reduce heat output while only sacrificing a small fraction of performance (often a worthwhile trade-off). Also, periodically dust out your rigs; clean hardware runs cooler and faster.
GPU Considerations
If you mine with a GPU (Qubic supports both CPU and GPU mining, even concurrently), remember that VRAM and drivers matter. Qubic’s AI models can be memory-hungry, so GPUs with 8–12 GB VRAM or more are recommended . NVIDIA RTX 30/40-series is a proven choices. Keep your GPU drivers up to date – driver optimizations can improve AI workloads. For multi-GPU rigs, ensure your power supply can handle the load and that cards are spaced for airflow. You may also limit each GPU’s power target (e.g., 80% TDP) to improve efficiency and thermals with minimal performance hit. If running hybrid CPU+GPU mining, watch your total system power and heat: a maxed-out CPU next to one or more busy GPUs in the same case can raise ambient temperatures, affecting both. In such cases, extra cooling or lowering one component’s usage (for example, using slightly fewer CPU threads when the GPU is also active) can prevent thermal bottlenecks.
OS-Level Tuning
Small software tweaks can yield performance gains. On Windows, set your Power Options to “High Performance” or “Ultimate Performance” so the CPU doesn’t downclock aggressively . Disable any “eco” or “cool & quiet” modes if you want maximum output.
Reminder: Plan configs around AVX-512 support and sustained, non-throttling all-core clocks.