Linux Kernel and Linux Foundation

• Two Powerful SSD Benchmark Utilities for Linux

  The 21^st century has seen unprecedented growth in the technological sector, and many upgrades have been made in the past several years. The evolution of phones from landlines to smartphones is a clear indicator of this technological phenomenon. The latter has become a key part of our lives, providing us a means to connect with the world around us. The desktops and laptops that we use today have also seen major progression, and this can be observed in the improvement in the quality of tools and games in the world of computers. One such sector in the computer world is that of memory storage, which has quickly moved on from traditional hard disks to a newer, faster type of storage called a solid-state drive, or SSD for short. SSDs are extremely fast, require less power, and are more shock-resistant than HDDs. You can see this for yourself by benchmarking your SSDs. Benchmarking is the process of measuring the performance of any tool, which can be done using a benchmarking utility. This article looks at two of the best utilities available for SSD benchmarking in the Linux operating system, Disks and hdparm.

• Radeon ROCm 4.0.1 Released For AMD Open-Source GPU Compute

  Last month marked the release of the big Radeon Open eCosystem 4.0 update (ROCm 4.0) while today that has been replaced by a v4.0.1 point release. ROCm 4.0 brought CDNA / MI100 (Arcturus) compute support and other "Exascale Era" preparations in making this open-source GPU compute stack competitor more competitive with NVIDIA's CUDA. For now though it's still been leaving out the Navi GPU support.

• Linux Foundation Public Health Joins The Fight Against COVID-19 Pandemic

  Brian Behlendorf is one of the most respected luminaries of the open-source world. He has been heading the Linux Foundation’s Hyperledger project since its inception and recently took over additional responsibilities of the Linux Foundation Public Health.

Devices and Open Hardware Leftovers

• Rugged mini-PC dips into Elkhart Lake

  Neousys unveiled a fanless, 112 x 87 x 50mm “POC-40” computer with an up to 3.0GHz, dual-core Atom x6211E plus up to 32GB DDR4, 2x GbE, 4x USB, 3x M.2, and DP, 2x serial, and isolated DIO. Last month, Neousys announced one of the first Intel Elkhart Lake based embedded PCs with its ultra-compact (153 x 108 x 56mm) POC-400. The company has followed up with an even smaller (112 x 87 x 50mm) and similarly rugged POC-40 using the same 10nm processor family. The industrial, DIN-rail mountable mini-PC supports applications such as space-constrained factory data collection systems, rugged edge computers, and mobile gateways.

• Pipo W12 Arm Windows 10 Laptop finally launched for $422 and up

  The project provides a Debian image for the aforementioned Yoga C630, so with some efforts a port to Pipo W12 may be possible.

• Arduino Blog » Access control unit designed with a Raspberry Pi CM4 and an Arduino Micro

  Whether granting access to public transit or restricting unauthorized personnel in buildings, NFC card readers can be extremely useful. Although most might not consider how they work – and simply happy getting through a turnstile – there’s a lot going on behind the scenes. In his video, Daniel Raines shows off a pair of prototype access control units (ACUs) that he’s constructed. The two networked devices are each based on a Raspberry Pi Compute Module 4 along with an Arduino Micro that controls six relays to allow or deny entry, provide feedback, fire, and lock up.

  

• Arduino Blog » 2002 Audio TT dashboard gets a digital speedometer upgrade with a custom CAN bus shield

  While it’s hard to beat analog instruments for instantaneous automotive feedback, Finnish electrical engineering student Jussi Ristiniemi also wanted a digital speed readout on his 2002 Audi TT. His particular model normally uses the car’s controller area network (CAN) to transmit the radio station or CD track to the uppermost section of the digital display. For this speedometer mod, audio data was replaced with “KM/H” readings, supplied by the vehicle’s CAN bus system via an Arduino Nano and custom interface shield.

4MLinux 35.1 released.

This is a minor (point) release in the 4MLinux STABLE channel, which comes with the Linux kernel 5.4.85. The 4MLinux Server now includes Apache 2.4.46, MariaDB 10.5.8, and PHP 7.4.13 (see this post for more details). You can update your 4MLinux by executing the "zk update" command in your terminal (fully automatic process).

NumPy (Python) Series

• How to Use Python NumPy Array – Linux Hint

  Many libraries exist in Python to perform different types of tasks. NumPy is one of them. The full form of NumPy is Numerical Python, and it is mainly used for scientific computing. Multi-dimensional array objects can be defined by using this library that is called the Python NumPy array. Different types of functions exist in the NumPy library to create the array. NumPy array can be generated from the python list of numeric data, range of data, and random data. How NumPy array can be created and used to do different operations types have shown in this tutorial.

• How to Use Python NumPy arange() Function – Linux Hint

  Many functions exist in the Python NumPy library to perform different types of numerical and scientific operations. Creating different types of arrays for various purposes is one of the practical uses of the NumPy library. Python has a built-in function named arange() to create a list of sequential numbers. arange() is one of the array creation functions of the NumPy library to create an array of numeric ranges. The uses of the NumPy arange() function have explained in this tutorial.

• How to Use Python NumPy reshape() Function – Linux Hint

  NumPy library has many functions to work with the multi-dimensional array. reshape () function is one of them that is used to change the shape of any existing array without changing the data. The shape defines the total number of elements in each dimension. The array’s dimension can be added or removed, and the number of elements in each dimension can be modified by using the reshape() function. The one-dimensional array can be converted into a multi-dimensional array, but the multi-dimensional array can’t be converted into a one-dimensional array by this function. How to reshape() function works and its uses are explained in this tutorial.

• How to Use Python NumPy zeros() and ones() Functions – Linux Hint

  NumPy library is one of the useful libraries of python that can be used to create arrays. zeros() and ones() are the NumPy library functions to create two different arrays. zeros() function is used to create an array based on the particular shape and type. All array elements are initialized to 0, which is created by the zeros() function. ones() function works like the zeros() function. But the elements of the array created by the ones() function are initialized to 1. The uses of both functions have shown in this tutorial by using multiple examples.

• How to convert Python NumPy array to python list – Linux Hint

  Array object is used to store multiple values, and the list object is used in Python to do a similar task to an array object. NumPy array object is used to do different types of numerical operations in Python. The multi-dimensional array can be created by using this library. NumPy library has a built-in tolist() function to convert the NumPy array to the python list. This function does not take any argument and returns the python list. If the array is one-dimensional, then the function will return a simple python list. If the array is multi-dimensional, then the array will return the nested python list. If the array’s dimension is 0, then the function will return a python scalar variable instead of a list. How tolist() function can convert different types of NumPy array to python list is shown in this tutorial.

• How to install NumPy python development environment on Ubuntu – Linux Hint

  Python is a modern programming language now for supporting a large number of libraries. Various types of tasks can be done by using these libraries. NumPy is one of the useful libraries of Python to perform scientific operations. This library can be used to create a multi-dimensional array of objects. Different types of mathematical tasks can be done quickly using this library, such as sorting the array, reshaping array, statistical operation, arithmetical operations, etc. It works faster because it is developed by using the C programming language.

• Python Unittest Tutorial

  Unit testing is a testing method used in software engineering for individual units of any code. Users can put the individual tests to determine the status of the source and how much the code is suitable to be used. This way users can test the code quality. Testing is done once the process of development is complete. Users can also begin testing when the test script is to be verified based on the criteria of the testing. Developers are expected to write the manual types of the source code. Generally, manually writing unit testing codes is a hectic task but in Python, it is done using an in-built function called unittest.