Programming Ada: Atomics And Other Low-Level Details

Especially within the world of multi-threaded programming does atomic access become a crucial topic, as multiple execution contexts may seek to access the same memory locations at the same time. Yet the exact meaning of the word ‘atomic’ is also essential here, as there is in fact not just a single meaning of the word within the world of computer science. One type of atomic access refers merely to whether a single value can be written or read atomically (e.g. reading or writing a 32-bit integer on a 32-bit system versus a 16-bit system), whereas atomic operations are a whole other kettle of atomic fish.

Until quite recently very few programming languages offered direct support for the latter, whereas the former has been generally something that either Just Worked™ if you know the platform you are on, or could often be checked fairly trivially using the programming language’s platform support headers. For C and C++ atomic operations didn’t become supported by the language itself until C11 and C++11 respectively, previously requiring built-in functions provided by the toolchain (e.g. GCC intrinsics).

In the case of Ada there has been a reluctance among the language designers to add support for atomic operations to the language, with the (GNU) toolchain offering the same intrinsics as a fallback. With the Ada 2022 standard there is now direct support in the System.Atomic_Operations library, however.

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Programming Ada: Implementing The Lock-Free Ring Buffer

In the previous article we looked at designing a lock-free ring buffer (LFRB) in Ada, contrasting and comparing it with the C++-based version which it is based on, and highlighting the Ada way of doing things. In this article we’ll cover implementing the LFRB, including the data request task that the LFRB will be using to fill the buffer with. Accompanying the LFRB is a test driver, which will allow us to not only demonstrate the usage of the LFRB, but also to verify the correctness of the code.

This test driver is uncomplicated: in the main task it sets up the LFRB with a 20 byte buffer, after which it begins to read 8 byte sections. This will trigger the LFRB to begin requesting data from the data request task, with this data request task setting an end-of-file (EoF) state after writing 100 bytes. The main task will keep reading 8-byte chunks until the LFRB is empty. It will also compare the read byte values with the expected value, being the value range of 0 to 99.

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Programming Ada: Designing A Lock-Free Ring Buffer

Ring buffers are incredibly useful data structures that allow for data to be written and read continuously without having to worry about where the data is being written to or read from. Although they present a continuous (ring) buffer via their API, internally a definitely finite buffer is being maintained. This makes it crucial that at no point in time the reading and writing events can interfere with each other, something which can be guaranteed in a number of ways. Obviously the easiest solution here is to use a mutual exclusion mechanism like a mutex, but this comes with a severe performance penalty.

A lock-free ring buffer (LFRB) accomplishes the same result without something like a mutex (lock), instead using a hardware feature like atomics. In this article we will be looking at how to design an LFRB in Ada, while comparing and contrasting it with the C++-based LFRB that it was ported from. Although similar in some respects, the Ada version involves Ada-specific features such as access types and the rendezvous mechanism with task types (‘threads’).

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Programming Ada: Records And Containers For Organized Code

Writing code without having some way to easily organize sets of variables or data would be a real bother. Even if in the end you could totally do all of the shuffling of bits and allocating in memory by yourself, it’s much easier when the programming language abstracts all of that housekeeping away. In Ada you generally use a few standard types, ranging from records (equivalent to structs in C) to a series of containers like vectors and maps. As with any language, there are some subtle details about how all of these work, which is where the usage of these types in the Sarge project will act as an illustrative example.

In this project’s Ada code, a record is used for information about command line arguments (flag names, values, etc.) with these argument records stored in a vector. In addition, a map is created that links the names of these arguments, using a string as the key, to the index of the corresponding record in the vector. Finally, a second vector is used to store any text fragments that follow the list of arguments provided on the command line. This then provides a number of ways to access the record information, either sequentially in the arguments vector, or by argument (flag) name via the map.

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Programming Ada: Packages And Command Line Applications

In the previous installment in this series we looked at how to set up an Ada development environment, and how to compile and run a simple Ada application. Building upon this foundation, we will now look at how to create more complex applications, along with how to parse and use arguments passed to Ada applications on the command line (CLI). After all, passing flags and strings to CLI applications when we launch them is a crucial part of user interaction, as well as when automating systems as is the case with system services.

The way that a program is built-up is also essential, as well-organized code eases maintenance and promotes code reusability through e.g. modularity. In Ada you can organize subprograms (i.e. functions and procedures) in a declarative fashion as stand-alone units, as well as embed subprograms in other subprograms. Another option is packages, which roughly correspond to C++ namespaces, while tagged types are the equivalent of classes. In the previous article we already saw the use of a package, when we used the Ada.Text_IO package to output text to the CLI. In this article we’ll look at how to write our own alongside handling command line input, after a word about the role of the binding phase during the building of an Ada application.

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Programming Ada: First Steps On The Desktop

Who doesn’t want to use a programming language that is designed to be reliable, straightforward to learn and also happens to be certified for everything from avionics to rockets and ICBMs? Despite Ada’s strong roots and impressive legacy, it has the reputation among the average hobbyist of being ‘complicated’ and ‘obscure’, yet this couldn’t be further from the truth, as previously explained. In fact, anyone who has some or even no programming experience can learn Ada, as the very premise of Ada is that it removes complexity and ambiguity from programming.

In this first part of a series, we will be looking at getting up and running with a basic desktop development environment on Windows and Linux, and run through some Ada code that gets one familiarized with the syntax and basic principles of the Ada syntax. As for the used Ada version, we will be targeting Ada 2012, as the newer Ada 2022 standard was only just approved in 2023 and doesn’t change anything significant for our purposes.

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The I960: When Intel Almost Went RISC

The i960 KA/KB/MC/XA with the main functional blocks labeled. Click this image (or any other) for a larger version. Die image courtesy of Antoine Bercovici. Floorplan from The 80960 microprocessor architecture.
The i960 KA/KB/MC/XA with the main functional blocks labeled. Click this image (or any other) for a larger version. Die image courtesy of Antoine Bercovici. Floorplan from The 80960 microprocessor architecture.

From the consumer space it often would appear as if Intel’s CPU making history is pretty much a straight line from the 4004 to the 8080, 8088 and straight into the era of Pentiums and Cores. Yet this could not be further from the truth, with Intel having churned through many alternate architectures. One of the more successful of these was the Intel i960, which is also the topic of a recent article by [Ken Shirriff].

Remarkably, the i960 as a solid RISC (Reduced Instruction Set Computer) architecture has its roots in Intel’s ill-fated extreme CISC architecture, the iAPX 432. As [Ken] describes in his comparison between the i960 and 432, both architectures are remarkably similar in terms of their instruction set, essentially taking what it could from the 432 project and putting it into a RISC-y shape. This meant that although the i960 could be mistaken as yet another RISC CPU, as was common in the 1980s, but integrated higher-level features as well, such as additional memory protection and inter-process communication. Continue reading “The I960: When Intel Almost Went RISC”