I then created a standard 10 GB test file, and compressed that many, many times using different QoS and concomitant operations.
Apple compressor m1 free#
To investigate what QoS does I’ve built another version of my free compressor-decompressor utility Cormorant (available below) which lets you set the QoS for its tasks. These turn out to be integer values spread evenly between 9 and 33, respectively, which is strange in itself.* Trying to use integer values for which there are no names, such as 32 or 34, doesn’t work: macOS doesn’t recognise those values, and assigns the QoS -1, which lets the system decide which of the four defined levels to use.
When writing the code, the developer uses names for the levels of QoS, ranging from background (lowest) to userInteractive (highest). Two common features which they can specify are the maximum number of concurrent operations, and their importance, or Quality of Service (QoS), and it’s the latter which I focus on here.Īpple provides four QoS levels, and a fifth which leaves it up to macOS to decide.
Apple compressor m1 code#
An app has to perform work which will take time, so to avoid it blocking the user and work alongside other apps, the developer puts the code and data into an Operation, like a task, which can then be run on one or more cores at a time. Although this can be achieved in many different ways, for the sake of simplicity I here concentrate on operation queues using Apple’s Foundation framework, which you’re most likely to encounter in macOS apps.Īt their heart, the principle of these is fairly simple. Whether Intel or ARM cores, macOS has to manage how tasks are run side-by-side on the same processor. I’ve now been digging deeper, and this article is a summary of how Intel and M1 Macs deal with multiple tasks, priorities and resources under macOS, and how that influences our assessment of their speed.
Last week I showed fascinating screenshots of how M1 Macs can run background processes exclusively on their four ‘efficiency’ cores.
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