ssd

如果您正在使用或者准备购买固态硬盘(SSD)，肯定会其已经有了一定的了解。由于固态硬盘的结构和机械硬盘有本质的不同，固态硬盘要实现真正的性能发挥需要TRIM指令等一些特殊的手段。不过大多数人并不知道，或者并没有注意的是，除了某些较新的固态硬盘以外，分区以及格式化对于固态硬盘也有着极其重要的影响。如果您只是简单地用XP或者其他一些较老的工具对固态硬盘进行分区和格式化的话，得到的性能可能会只有几分之一！ 注：Intel的固态硬盘在控制器层面上对这个问题进行了自动补偿，因此如果您使用的是Intel的固态硬盘的话，可以跳过本文了。 ##一. 问题的根源 问题的根源要从固态硬盘的组成部分，闪存说起。目前的绝大多数闪存的组织结构是划分成很多个512KB的块(Block)，而每个块又由很多以4KB为单位的页(Page)组成。这就好像我国的行政组织是划分成众多个省，每个省又划分成很多个市一样。闪存的工作原理决定了它的擦除操作是以块(Block)为单位，而写入操作则是以页(Page)为最小单位。本站的固态硬盘技术专题可以让您更多地了解固态硬盘以及闪存。 另一方面，我们的操作系统在管理硬盘时也有一个最小分配单元。NTFS的默认的最小分配单元的大小恰好也是4KB，这很不错。不过问题在于，在进行分区时通常并不是从头开始的，而是有一个偏移值。比如使用Windows XP的分区工具的话

How can I, from a C program, read the hardware information of a drive? (I.e. to determine if the drive is an SSD or a mechanical disk.) SSD are supposed to identify themselves as non-rotative. For linux, as example, you can get the info via sysfs: cat /sys/block/sda/queue/rotational If it returns 0, you have SSD... Have you considered doing a read/write test to try to determine capabilities ? Jeremy Morgan You can use the GetDriveType Method from the win32 library, and you might be able to differentiate that way, or you use GetVolumeInformation to try and determine it from the label. This

自己在网上购置了所有电脑配件自行组装（硬盘为ssd固态硬盘），硬件一次性装好点亮无问题出现，但是在安装windows7 64位的时候出现：windows安装程序无法将windows配置为在此计算机的硬件上运行。 网上有很多解决办法：比如按shift+F10，我在出错界面键盘和鼠标已经失灵，无法做任何输入，不得不说网上大部分的解决办法都是无用的，最后自己动手解决问题了，以下是解决办法： 总结性：安装的时候用硬盘的ahci模式（bios中设置），第一次部分安装完成重启后，改成ide继续安装配置，全部完成后在windows下修改注册表 成ahci ，重启进入bios修改成ahci，重启后完成，以下为具体步骤： 在bios中先设置ssd硬盘的连接方式为：ahci模式，然后 保存 重启； 用windows pe安装windows，（我用的是老毛桃）正常格式化（注意硬盘格式用mbr类型），然后用windows安装程序正常安装64位； 第一次安装完成后重启（还未进入安装后的配置步骤），再次进入bios，将硬盘模式改成：ide模式 ，然后保存重启 ； 继续配置安装直到完成，不再提示错误； 安装完成之后，首先要修改注册表（不修改注册表的话ahci模式会蓝屏）：HKEY_LOCAL_MACHINE/System/CurrentControlSet/Services

I trained SSD using TensorFlow Object Detection API as described here . It produces a ckpt, meta and index file. In order to run it on my images I tried to check the demo code. It requires that the model be converted to frozen graph. I tried to convert my model to a frozen inference graph as described here . In that program I have to provide output node names. I could not figure out the name of the node in the SSD model which must be used here. Please help. I tried 'num_detections:0', 'detection_boxes:0' etc. Only to get error: AssertionError: num_detections is not in graph Jonathan Huang We

I use ssd_mobilenets in Object detection API to train my own model, and get .ckpt files. It works well on my computer, but now I want to use the model on my phone. So, I need convert it to .pb file. I do not know how to do it, can any one help? By the way, the graph of ssd_mobilenets is complex, I can not find which is the output of model. Is there any one knowing the name of the output? Use export_inference_graph.py to convert model checkpoint file into a .pb file. python tensorflow_models/object_detection/export_inference_graph.py \ --input_type image_tensor \ --pipeline_config_path

I want to try to speed up my compile-time of our C++ projects. They have about 3M lines of code. Of course, I don't need to always compile every project, but sometimes there are lot of source files modified by others, and I need to recompile all of them (for example, when someone updates an ASN.1 source file). I've measured that compiling a mid-project (that does not involves all the source files) takes about three minutes. I know that's not too much, but sometimes it's really boring waiting for a compile.. I've tried to move the source code to an SSD (an old OCZ Vertex 3 60 GB) that,