In this article, I'm covering something that's a littleabstruse: converting numeric bases within shell scripts. There arereally four commonly used numeric bases to consider: binary, octal,decimal and hexadecimal. You're used to working in base-10, so 10 =1 * 10**1 + 0 and 100 = 1 * 10**2 + 0 * 10**1 + 0.
That maps to other numeric bases, so 1010 base-2 or binary is really 1 *2**3 + 0 * 2**2 + 1 * 2**1 + 0 or 8 + 0 + 2 + 0 = 10 decimal. Octal isthe same thing, so 33 base-8 converts to decimal as 3 * 8**1 + 3 = 27.
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Hexadecimal presents a different challenge because a base-16numbering system doesn't fit neatly into our Arabic numerals 0, 1, 2,... 9. "Hex", as it's known informally, adds A, B, C, D, E and F,so that the decimal value 10 is represented in Hex as "A".That'swhere the math gets interesting, so 33 base-16 = 3 * 16**1 + 3 = 48 +3 = 51.
The long, complicated way to create a base conversion utility istherefore to disassemble every value given and apply the translationshown, then have an internal value that's a common base (probablybase-10), then have another routine that converts the common base tothe desired output base.
A common numeric notation in the Linux world is to recognize that numbersprefaced with a zero are octal, and those prefaced with "0x" arehexadecimal. (Binary isn't particularly useful so it's not includedin the common notation.) Here are a few examples: 0700, 0xFFc39. You could modifythe script to accept these as inputs and infer the appropriate base,but I'm going to leave that as an exercise for you, dear reader.
But, I'm not done yet. There's one more way you can convert values,and it's actually directly within the shell. It turns out that using the$(( )) notation, you actually can specify a numericbase for numbers!
If you don't care about binary values, you can see that there are threecompletely different ways to convert numeric bases from within a shellscript. Now take what I've shown here and do something really slick!
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Amazon EC2 allows you to set up and configure everything about your instances from your operating system up to your applications. An Amazon Machine Image (AMI) is simply a packaged-up environment that includes all the necessary bits to set up and boot your instance. Your AMIs are your unit of deployment. You might have just one AMI or you might compose your system out of several building block AMIs (e.g., webservers, appservers, and databases). Amazon EC2 provides a number of tools to make creating an AMI easy. Once you create a custom AMI, you will need to bundle it. If you are bundling an image with a root device backed by Amazon EBS, you can simply use the bundle command in the AWS Management Console. If you are bundling an image with a boot partition on the instance store, then you will need to use the AMI Tools to upload it to Amazon S3. Amazon EC2 uses Amazon EBS and Amazon S3 to provide reliable, scalable storage of your AMIs so that we can boot them when you ask us to do so.
Amazon EC2 is transitioning On-Demand Instance limits from the current instance count-based limits to the new vCPU-based limits to simplify the limit management experience for AWS customers. Usage toward the vCPU-based limit is measured in terms of number of vCPUs (virtual central processing units) for the Amazon EC2 Instance Types to launch any combination of instance types that meet your application needs.
You are limited to running one or more On-Demand Instances in an AWS account, and Amazon EC2 measures usage towards each limit based on the total number of vCPUs (virtual central processing unit) that are assigned to the running On-Demand instances in your AWS account. The following table shows the number of vCPUs for each instance size. The vCPU mapping for some instance types may differ; see Amazon EC2 Instance Types for details.
The AWS Graviton2 processors deliver up to 7x performance, 4x the number of compute cores, 2x larger caches, 5x faster memory, and 50% faster per core encryption performance than first generation AWS Graviton processors. Each core of the AWS Graviton2 processor is a single-threaded vCPU. These processors also offer always-on fully encrypted DRAM memory, hardware acceleration for compression workloads, dedicated engines per vCPU that double the floating-point performance for workloads such as video encoding, and instructions for int8/fp16 CPU-based machine learning inference acceleration. The CPUs are built utilizing 64-bit Arm Neoverse cores and custom silicon designed by AWS on the advanced 7 nm manufacturing technology.
In order to enable this feature, you must launch an HVM AMI with the appropriate drivers. The instances listed as current generation use ENA for enhanced networking. Amazon Linux AMI includes both of these drivers by default. For AMIs that do not contain these drivers, you will need to download and install the appropriate drivers based on the instance types you plan to use. You can use Linux or Windows instructions to enable Enhanced Networking in AMIs that do not include the SR-IOV driver by default. Enhanced Networking is only supported in Amazon VPC.
The number of instances you are allowed to reserve is based on your account's On-Demand instance limit. You can reserve as many instances as that limit allows, minus the number of instances that are already running.
Amazon EC2 instances are grouped into 5 families: General Purpose, Compute Optimized, Memory Optimized, Storage Optimized and Accelerated Computing instances. General Purpose Instances have memory to CPU ratios suitable for most general purpose applications and come with fixed performance or burstable performance; Compute Optimized instances have proportionally more CPU resources than memory (RAM) and are well suited for scale out compute-intensive applications and High Performance Computing (HPC) workloads; Memory Optimized Instances offer larger memory sizes for memory-intensive applications, including database and memory caching applications; Accelerated Computing instances use hardware accelerators, or co-processors, to perform functions such as floating point number calculations, graphics processing, or data pattern matching, more efficiently than is possible in software running on CPUs; Storage Optimized Instances provide low latency, I/O capacity using SSD-based local instance storage for I/O-intensive applications, as well as dense HDD-storage instances, which provide local high storage density and sequential I/O performance for data warehousing, Hadoop and other data-intensive applications. When choosing instance types, you should consider the characteristics of your application with regards to resource utilization (i.e. CPU, Memory, Storage) and select the optimal instance family and instance size.
First, the NVMe device names used by Linux based operating systems will be different than the parameters for EBS volume attachment requests and block device mapping entries such as /dev/xvda and /dev/xvdf. NVMe devices are enumerated by the operating system as /dev/nvme0n1, /dev/nvme1n1, and so on. The NVMe device names are not persistent mappings to volumes, therefore other methods like file system UUIDs or labels should be used when configuring the automatic mounting of file systems or other startup activities. When EBS volumes are accessed via the NVMe interface, the EBS volume ID is available via the controller serial number and the device name specified in EC2 API requests is provided by an NVMe vendor extension to the Identify Controller command. This enables backward compatible symbolic links to be created by a utility script. For more information see the EC2 documentation on device naming and NVMe based EBS volumes.
Optimize CPUs gives you greater control of your EC2 instances on two fronts. First, you can specify a custom number of vCPUs when launching new instances to save on vCPU-based licensing costs. Second, you can disable Intel Hyper-Threading Technology (Intel HT Technology) for workloads that perform well with single-threaded CPUs, such as certain high-performance computing (HPC) applications.
After you download and install the ODBC driver, add a data source name (DSN) entry to the client computer or Amazon EC2 instance. SQL client tools use this data source to connect to the Amazon Redshift database.
[The rest of this paragraph is only relevant after release.]The bin/windows directory of a CRAN site containsbinaries for a base distribution and a large number of add-on packagesfrom CRAN to run on 64-bit Windows.
WebP includes the lightweight encoding and decoding library libwebpand the command line tools cwebp and dwebp for convertingimages to and from the WebP format, as well as tools for viewing, muxing andanimating WebP images. The full source code is available on thedownload page.
Packages made for older distributions may work on newer distributions as long as nothing substantial has changed (i.e. Python version). Also there are several distributions out there that are based on one in the above list (e.g. Linux Mint which is based on Ubuntu). This means that packages for that base distribution should also work on derivatives, you just need to know which version the derivative is based upon and pick your download accordingly. 2ff7e9595c
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