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Will display the memory information in megabytes.free -m commandYou can also use the “free -g” option to display the memory information in gigabytes.free -g commandMethod 5: Using the “vmstat” commandThe vmstat command is a Linux utility that displays information about the virtual memory on a system.To use the “vmstat” command, open a terminal and type:vmstat -svmstat -s commandThe vmstat command with the -s option displays a variety of statistics about memory, paging, block IO, traps, and CPU activity.The statistics displayed by vmstat are:Memory usage: total amount of free and used memory in the system, as well as the amount of memory used by the kernel.Paging: amount of paging activity in the system, including the number of page faults, the number of pages swapped out, and the number of pages used by the kernel.Block IO: amount of block IO activity in the system, including the number of blocks read and written.Traps: number of traps received by the kernel, including interrupts, system calls, and exceptions.CPU activity: amount of time the CPU spends in various states, including user time, system time, and idle time.You can also use the “vmstat -d” option to display the detailed information about the virtual memory.vmstat -d commandConclusionIn conclusion, checking the amount of memory that is being used is an important part of computer management. Ubuntu offers a number of easy-to-use and approachable GUI tools to check memory usage, while the “htop”, “cat”,”free”,”vmstat” commands are also accessible in the terminal.

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Defeat Cubes 2048.io players! This is a number battle where you don't use weapons or body to fight. Just move and collect to get as high numbers as you can.Play Cubes 2048.io onlineIn my opinion, this is one of the most fun multiplayer games in the world. This game allows you to fight with many players worldwide. In this game, you will do two main actions which are to collect blocks and attack opponents.Collect blocksYou are the original block and there are many different blocks on the ground. Your block will contain a number and you can collect the blocks with lower or the same numbers as your number. When these blocks become your tail, they will immerse the same numbers together. From that, the numbers of the original block will increase gradually.Beat opponentsYou only attack the opponents who have a lower number on their original blocks than yours. You must boost your speed to escape from opponents who have a higher number than yours.Cubes 2048.io world recordGaining the Cubes 2048.io world record is very hard because there are many pro players who will join the battles. You have to show who you are and get first place as a leader of the match. You can use the boost pads to slide more quickly. Some double pads can double your numbers and the split squares will reduce your number. Let's have fun with numbers now!

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Be diagnosed by simply looking at the Log Growths performance counter in the SQL Server, Databases Object, if is anything but 0 it means log auto-growth had occurred at least once. Real-time monitoring can be done by watching for Data File Auto Grow Event Class and Log File Auto Grow Event Class events in SQL Profiler.I did not cover many wait types here (eg. CLR_*, SQLCLR_*, SOSHOST_*, HADR_*, DTC_* and many more). If you encounter a wait type you do not understand, usually just searching online for its name will reveal information about what that wait type is what potential bottleneck it indicates, if any.Analyze disk activity: IO statsSQL Server needs to read and write to the disk. All writes (inserts, updates, deletes) must be written to disk. Queries always return data from the in-memory cache (the buffer pool) but the cache may not contain the desired data and has to be read from disk. Understanding if the IO is a bottleneck for your performance is a necessary step in any performance investigation. SQL Server collects, aggregates and exposes information about every data and log IO request. First thing I like to look at is sys.dm_io_virtual_file_stats. This DMV exposes the number of writes and reads on each file for every database in the system, along with the aggregated read and write IO ‘stall’ times. Stall times are the total time tasks had to block waiting for transfer of data to and from disk.select db_name(io.database_id) as database_name, mf.physical_name as file_name, io.* from sys.dm_io_virtual_file_stats(NULL, NULL) iojoin sys.master_files mf on mf.database_id = io.database_id and mf.file_id = io.file_idorder by (io.num_of_bytes_read + io.num_of_bytes_written) desc;The per file IO stats are aggregated since server start up but be aware that they reset for each file if it ever goes offline. The total number of bytes transferred (reads. To block websites on Chrome, To manage the blocked site, click the BlockSite extension icon. iOS users also have the free option of going into the iOS settings and blocking sites using the

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Driver modules to blacklist for nvidia-fs "drivers": [ ], // specify list of block devices to prevent IO using libcufile "devices": [ ], // specify list of mount points to prevent IO using libcufile // (e.g. ["/mnt/test"]) "mounts": [ ], // specify list of file-systems to prevent IO using libcufile // (e.g ["lustre", "wekafs", "vast"]) "filesystems": [ ] } // Application can override custom configuration via // export CUFILE_ENV_PATH_JSON= // e.g : export CUFILE_ENV_PATH_JSON="/home//cufile.json" }4.3. GPUDirect Storage Benchmarking Tools#There are several storage benchmarking tools and utilities for Linux systems, with varying degrees offeatures and functionality. The fio utility is one of the morepopular and powerful tools that is used to generate storage IO loads and offers significant flexibilityfor tuning IO generation based on the desired IO load characteristics. For those familiar with fio onLinux systems, the use of gdsio will be very intuitive.Since GDS is relatively new technology, with support dependencies and a specific set of libraries and APIsthat fall outside standard POSIX IO APIs, none of the existing storage IO load generation utilities includeGDS support. As a result, the installation of GDS includes the gdsio load generator which providesseveral command line options that enable generating various storage IO load characteristics via both thetraditional CPU and the GDS data path.4.3.1. gdsio Utility#The gdsio utility is similar to a number of disk/storage IO load generating tools. It supports a seriesof command line arguments to specify the target files, file sizes, IO sizes, number of IO threads, and so on.Additionally, gdsio includes

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In this program we will see how we can download image from an URL in java language.For that we will be using this image at the URLImage Source: download an image from the internet we first need the URL of the image. After that we need to read the image from the site and then write it into our system storage.Method-1: Java Program to Download Image From an URL By Using Input and OutputStreamApproach:Use a try catch block to catch any IO errors caused .Store the URL of the image in an URL object and store the path to save the file in a string.Create an InputStream object on the URL provided to fetch the image by using openStream() method and an OutputStream object on the download path to store the object.Use a while loop till the EOF to copy the image from the InputStream object to the FileOutputStream object.Close the stream objects and print the path of the image on successful download.Program:package btechgeeks;import java.io.FileOutputStream;import java.io.IOException;import java.io.InputStream;import java.io.OutputStream;import java.net.URL;public class Main{ public static void main(String[] args) { //Try catch block to catch any IO error thrown try { //URL of the image URL link = new URL (" //The path to store the downloaded image into String downloadPath = "D:\\ImageProgram/downloadedImage.jpg"; //Using inputStream to read the image from the URL InputStream is = link.openStream(); //Saving the image into the path specified OutputStream fos = new FileOutputStream(downloadPath); int ch; //Loop until all the data from the image is copied and we reach the EOF while ((ch = is.read()) != -1) { fos.write(ch); } //Output statement to execute upon successful download System.out.println("Your image has been downloaded successfully and is stored at " +downloadPath); //Close the objects. is.close(); fos.close(); } //Catch block to catch IO errors catch(IOException e) { e.printStackTrace(); } }}Output:Your image has been downloaded successfully and is stored at D:\ImageProgram/downloadedImage.jpgIn File Explorer-Method-2: Java Program to Download Image From an URL By Using ImageIOSyntax:ImageIo.write(imageObj,extension,image,FileObject )Where,imageObj – Image object is the object we have stored the fetched image inExtension – Extension is the extension of the file i.e. jpg, jpeg, png etcFileObject- It is the file we are storing the file in.Approach:Create an object of BufferedImage.Inside a try catch block, store the image url in an URL object.Fetch the image from the url using ImageIO.read( ) method.Write to the file using ImageIo.write( ) method.Program:package btechgeeks;import java.io.FileOutputStream;import java.io.IOException;import javax.imageio.ImageIO;import java.awt.image.BufferedImage;import java.io.File;import java.net.URL;public class Main{ public static void main(String[] args) { // Create an BufferedImage object to store the image BufferedImage img = null; // Try catch block to catch any IO error thrown try { // Image Link URL link = new URL(" // Read image from the link img = ImageIO.read(link); // Write the

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GPU 0. Changing the GPU from 0 to 8:nfs_client> gdsio -D /mnt/nfs/ib0/data/0/gds_dir -d 8 -w 32 -s 1G -i 1M -x 0 -I 0 -T 120IoType: READ XferType: GPUD Threads: 32 DataSetSize: 1053419520/33554432(KiB) IOSize: 2048(KiB) Throughput: 8.352013 GiB/sec, Avg_Latency: 7480.408305 usecs ops: 514365 total_time 120.284676 secsWe note again a decrease in throughput (8.3GB/sec from 9.5GB/sec) and increase in latency (3.4ms to 7.5ms).Using the supported gdsio config files facilitates an easily reusable “tool box” of IO loads andconfigurations. Also, with multiple jobs running, gdsio will aggregate the results, making it easierto see the complete performance picture.Here’s a sample configuration file to generate 4k random reads to multiple NFS mount points for 4 differentGPUs. Note various parameters defined in the global section, then job-specific parameters (GPU, targetmount point, number of threads) in each job section.[global]name=nfs_random_read#0,1,2,3,4,5xfer_type=0#IO type, rw=read, rw=write, rw=randread, rw=randwriterw=randread#block size, for variable block size can specify range e.g. bs=1M:4M:1M, (1M : start block size, 4M : end block size, 1M :steps in which size is varied)bs=4k#file-sizesize=500M#secsruntime=120[job1]#numa nodenuma_node=0#gpu device index (check nvidia-smi)gpu_dev_id=0num_threads=16directory=/mnt/nfs/ib0/data/0/gds_dir[job2]numa_node=0gpu_dev_id=2num_threads=16directory=/mnt/nfs/ib1/data/0/gds_dir[job3]numa_node=0gpu_dev_id=4num_threads=16directory=/mnt/nfs/ib2/data/0/gds_dir[job4]numa_node=0gpu_dev_id=6num_threads=16directory=/mnt/nfs/ib3/data/0/gds_dirExecuting gdsio using the above config file, simply pass the file name as the only argument:nfs_client> gdsio nfs_rr.gdsioIoType: RANDREAD XferType: GPUD Threads: 64 DataSetSize: 277467756/32768000(KiB) IOSize: 4(KiB) Throughput: 2.213928 GiB/sec, Avg_Latency: 110.279539 usecs ops: 69366939 total_time 119.522363 secsThe sustained random read rate was about 580k IOPS (69366939 / 119.52).For throughput testing, the load attributes need to be changed so gdsio issues reads and writes, notrandom reads and random writes (see rw=in the global section). Also, the IO size (bs= in theglobal. To block websites on Chrome, To manage the blocked site, click the BlockSite extension icon. iOS users also have the free option of going into the iOS settings and blocking sites using the Free the Web from ads and protect your privacy with AdGuard Browser Extension for iOS AdGuard for iOS Pro Block ads in Chrome Block ads in Firefox Block ads in Safari Block ads in Edge

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Main memory. The performance benefit of the page cachecan be substantial, as a typical two CPU socket system can read/write system memory at significantly higherthroughput and lower latency than storage.The file system-specific settings and tuneable parametersFile system-specific settings/parameters can happen at both creation time (mkfs) and at mount time in the formof mount options. Some mount options are file system independent (for example, atime, async, and so on),while other options are specific to the file system. Any performance evaluation of the storage technology requiresbypassing the page cache to ensure that actual storage performance is being measured, and not the page cache read/write performance.GDS currently supports the ext4 file system on Linux, and requires the use of the O_DIRECT flag on files thatare targeted for read/write by the GDS IO APIs. With O_DIRECT set, you can bypass the system’s page cache.Another factor in assessing storage performance results are the IO characteristics, which are historically categorized as:Random IO (small IO size)Sequential IO (large IO size)The terms random and sequential refer to the on-disk block layout of the target files and are relevant when assessingstorage that uses hard disk drives (HDDs). HDD technology implements spinning disks with read/write heads that performseek operations to locate the target blocks where the data is to be read or written. This seek time induces IO latencydue to electro-mechanical delays, (moving the read/write heads around the platters). With Solid State Disks (SSDs), nosuch electro-mechanical exist, so sequential versus random IO on SSDs is not a consideration in terms

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And writes) is a good indicator of how busy is a database from IO point of view. The stalls indicate which IO subsytem (which disk) is busy and may even be saturated. Analyzing individual query executionWhen analyzing an individual statement or query for performance allows us to understand what the query is doing, how much is executing vs. what is waiting on. The most simple analysis is to use the execution statistics. These work by first running the appropriate SET STATISTICS ... ON in your session and then executing the statement or query you want to analyze. In addition to the usual result, the query will also report execution statistics, as follows:SET STATISTICS TIME ONThe query parse time, compile time and execution time are reported. If you execute a batch or a stored procedure with multiple statements then you get back the time for each statement, which helps determining which statement in a procedure is the expensive one. But we’ll see that analyzing the execution plan reveals the same information, and more.SET STATISTICS IO ONThe IO statistics show, for each statement, the number of IO operations. The result shows several metrics for each table touched by the statement:scan countNumber of times the scans or seeks were started on the table. Ideally each table should be scanned at most once.logical readsNumber of data pages from which rows were read from the in-memory cache (the buffer pool).physical readsNumber of data pages from which data was had to be transferred from disk in-memory cache (the buffer pool) and the task had to block and wait for the transfer to finish.read-ahead readsNumber of data pages that were asynchronously transferred from disk into the buffer pool opportunistically and the task did not had to wait for the transfer.LOB logical/physical/read-ahead readsSame as their non-lob counterparts, but