دانلود Thermo Scientific Avizo Trueput 2024.1 x64 نرم افزار کنترل کیفیت باطری

System Requirements
Thermo Scientific Avizo Trueput Software runs on:
Microsoft Windows® 10 (64-bit) and Microsoft Windows® 11 (64-bit).

Prioritizing hardware for Avizo Trueput Software
Introduction
This document provides recommendations about choosing a suitable workstation to run Avizo Trueput Software.

The four most important components to consider are the graphics card (GPU), the CPU, the RAM, and the hard drive.

Because the hardware requirements will widely vary according to the size of your data and your workflow, we strongly suggest that you take advantage of our supported evaluation version to try working with one of your typical data sets.

Graphics Cards
Avizo Trueput Software should run on any graphics system (this includes the GPU and its driver) that provides a complete implementation of OpenGL 4.2 or higher. However, graphics board and driver bugs are not unusual.

The amount of GPU memory needed depends on the size of the data. We recommend a minimum of 1 GB on the card. Some visualization modules may require graphics memory large enough to hold the actual data.

All driver bugs are submitted to the vendors. A fix may be expected in a future driver release. Due to vendor support policies, we are not able to commit to providing a fix for bugs caused by the driver on standard graphics boards. We recommend using a professional graphics board to benefit from the professional support offered by the vendors (driver bugs fixes, etc.).

List of tested GPUs:
Vendor
Model

NVIDIA       
Quadro P400, Quadro RTX 4000, Quadro T1200 Laptop GPU

Intel
UHD 630, UHD 770

System Memory
System memory is the second most important determinant for processing large data with Avizo Trueput Software.

You may need much more memory than the actual size of the data you want to load within Avizo Trueput Software. Some processing may require several times the memory required by the original data set. If you want to load, for instance, a 4 GB data set in memory and apply a non-local means filter to the original data and then compute a distance map, you may need up to 16 or 20 GB of additional memory for the intermediate results of your processing. It is common to need two to three times the memory footprint of the data being processed for basic operations. For more complex workflows, you may need up to six or eight times the memory (e.g. 32 GB may be required for a 4 GB dataset).

Similarly, the size of the data on disk may be much smaller than the memory needed to load the data as the file format may have compressed the data (for instance, loading a stack of JPEG files).

Hard Drives
When working with large files, reading data from the disk can slow down your productivity. A standard hard drive (HDD) (e.g., 7200rpm SATA disk) can only stream data to your application at a sustained rate of about 60 MB/second. That is the theoretical limit; your actual experience is likely to be closer to 40 MB/second. To read a 1 GB file from the disk, you will likely have to wait 25 seconds. For a 10 GB file, the wait is 250 seconds, over four minutes. Large data technologies will greatly reduce the wait time for data visualization, but disk access will still be a limiting factor when you want to read data files at full resolution for data processing. Compared to traditional HDDs, solid state drives (SSD) can improve read and write speeds.

Reading data across a network, for example from a file server, will normally be much slower than reading from a local disk. The performance of your network depends on the network technology (100 Mb, 1 Gb, etc.), the amount of other traffic on the network, and the number and size of other requests to the file server. Remember, you are (usually) sharing the network and server and will not get the theoretical bandwidth. Large data technologies may also facilitate visualization of volume data through the network, but if data loading is a bottleneck for your workflow, we recommend making a local copy of your data.

CPU
While Avizo Trueput Software mostly relies on GPU performance for visualization, many modules are computationally intensive and their performance will be strongly affected by CPU performance.

More and more modules inside Avizo Trueput Software are multi-threaded and thus can take advantage of multiple CPUs or multiple CPU cores available on your system. This is the case for most of the quantification modules provided with Avizo Trueput Software and various computation modules.

CPU clock speed, number of cores, and memory cache are the three most important factors affecting the performance of Avizo Trueput Software. While most multi-threaded modules will scale up nicely according to the number of cores, the scaling bottleneck may come from memory access. For example, up to eight cores show almost linear scalability while more than eight cores do not show much gain in performance. A larger memory cache will improve performance.