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3.6. Playback Speed Factors for Multi-Z Plane Image Sequences

Playback Speed Factors for Multi-Z Plane Image Sequences

When playing through a time-series dataset in Volocity, you may notice that playback is smoother in the XY plane mode, but significantly slower in XYZ, XZ, or YZ viewing modes. This difference arises from how image data is stored and processed, as well as the hardware performance of the system.

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Why Is Playback Slower in XYZ, XZ, and YZ Views?

1. Memory Caching and Resource Usage

• On first playback, the entire image volume is loaded from the storage device into memory.
• Subsequent playback for the same timepoints benefits from cached memory, improving performance.
• However, when playing through many timepoints, the memory cache may reach its limit, causing older data to be pushed out and reloaded from storage, reducing the cache's effectiveness.

2. Memory Layout of Z Planes

• XY planes are stored sequentially in memory for efficient access. For example:

  • A simple 3x3 XY plane filled with zeros is stored in memory as:
    0 0 0 0 0 0 0 0 0.

• 3D Volumes (multiple XY planes) are stored as a linear block:

  • 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2.

• To display XZ or YZ planes, Volocity must extract specific voxels from the 3D block and rearrange them into a format suitable for display (e.g., an XZ plane appears in memory as 0 1 2 0 1 2 0 1 2).

  • This extraction and rearrangement process is computationally intensive, especially for large datasets.
  • For datasets with many Z planes (e.g., 100 or more), extracting the XZ or YZ planes is significantly slower than displaying a single XY plane.

3. Dataset Size and Disk Throughput

• Large datasets require high-speed storage to minimize delays in loading data. For example:
  • A 22GB dataset with timepoints sized at 700MB will take longer to load if stored on older storage systems.
  • The first playback may take longer as the dataset is loaded into memory from disk.

Example Calculation:

For a 700MB timepoint stored on modern NVMe SSDs with a read speed of 3,500MB/s:

• Time to load each timepoint = Size of timepoint ÷ Disk speed
  • 700MB ÷ 3,500MB/s ≈ 0.2 seconds per timepoint

In comparison, older storage systems (e.g., HDDs or SATA SSDs) with slower read speeds (e.g., 100MB/s) would take significantly longer (700MB ÷ 100MB/s = 7 seconds per timepoint).

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Modern Hardware Recommendations for 2025

To achieve optimal playback speeds, consider upgrading your system with modern hardware:

1. Use NVMe SSDs:

   • NVMe SSDs provide sequential read speeds of 3,000–7,000MB/s, far outperforming older RAID or SATA SSD setups.
   • Example drives: Samsung 980 Pro, Western Digital SN850X, or enterprise-grade NVMe drives for heavy workloads.

2. Increase System RAM:

   • More RAM allows larger datasets to be cached in memory, reducing the need to reload data from disk.
   • For large datasets (e.g., 22GB or larger), consider at least 64GB or 128GB of RAM.

3. Free Up Disk Space:

   • Keep storage drives at least 30-40% free to prevent latency from disk fragmentation or overuse.

4. Upgrade to PCIe 5.0 or 4.0 Storage Interfaces:

   • PCIe 5.0 and 4.0 NVMe drives offer higher bandwidth, reducing data transfer times for large datasets.

5. GPU Acceleration:

   • Modern GPUs with CUDA support (e.g., NVIDIA RTX 4000/5000 series or A-series professional GPUs) can offload some computational tasks, improving processing times for rendering XYZ, XZ, and YZ planes.

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How to Optimize Your Workflow:

1. Optimize Cache Usage:

   • Play through smaller ranges of timepoints at a time to make the most of cached memory.

2. Minimize AV Interference:

   • If using Windows Defender or institutional antivirus, exclude Volocity directories and data files from real-time scanning. This can improve performance during initial playback.

3. Check Disk Throughput:

   • Use modern benchmarking tools (e.g., CrystalDiskMark) to verify disk read/write speeds.
   • Ensure your storage setup is meeting expected performance levels.

4. Monitor Hardware Resources:

   • Use system monitoring tools (e.g., Task Manager, HWInfo) to ensure no bottlenecks in CPU, GPU, or RAM usage during playback.

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Key Takeaways:

• Playback performance is heavily influenced by storage speed, RAM availability, and dataset size.
• Upgrading to NVMe SSDs, increasing RAM, and optimizing antivirus settings can significantly improve playback performance.
• For very large datasets, consider systems with high-speed storage interfaces (e.g., PCIe 5.0 NVMe drives) and professional GPUs to reduce computational overhead.

By leveraging modern hardware and optimizing system configurations, you can achieve smoother playback and improved performance in Volocity, even with large multi-Z plane datasets.