D-Wave Systems has released an open source quantum computing chunk of software.
Quantum computing, as we know, moves us on from the world of mere 1’s and 0’s in binary to the new level of ‘superposition’ qubits that can represent many more values and therefore more computing power — read this accessible piece for a simple explanation of quantum computing.
Because of my long-standing association with the Apache Software Foundation, I’m often asked the question, “What’s next for open source technology?” My typical response is variations of “I don’t know” to “the possibilities are endless.”
Over the past year, we’ve seen open source technology make strong inroads into the mainstream of enterprise technology. Who would have thought that my work on Hadoop ten years ago would impact so many industries – from manufacturing to telecom to finance. They have all taken hold of the powers of the open source ecosystem not only to improve the customer experience, become more innovative and grow the bottom line, but also to support work toward the greater good of society through genomic research, precision medicine and programs to stop human trafficking, as just a few examples.
Below I’ve listed five tips for folks who are curious about how to begin working with open source and what to expect from the ever-changing ecosystem.
In this podcast, the Radio Free HPC team looks at D-Wave’s new open source software for quantum computing. The software is available on github along with a whitepaper written by Cray Research alums Mike Booth and Steve Reinhardt.
Marina Paych was a newcomer to open source software when she left a non-governmental organization for a new start in the IT sector—on her birthday, no less. But the real surprise turned out to be open source. Fast forward two years and this head of organizational development runs an entire department, complete with a promotional staff that strategically markets her employer's open source web development services on a worldwide scale.
You can install databases such as MySQL, PostgreSQL, or even MongoDB very quickly thanks to package management, but the installation is not even half the battle. A functioning database also needs user accounts and several configuration steps for better performance and security.
This need for additional configuration poses challenges in cloud environments. You can always manually install a virtual machine in traditional settings, but cloud users want to generate an entire virtual environment from a template. Manual intervention is difficult or sometimes even impossible.
“Usually access networks include all kinds of encryption and tunneling protocols,” says Fite. “It’s not a standard, native-IP environment.” Saguna’s platform creates a bridge between the access network to a small OpenStack cloud, which works in a standard IP environment. It provides APIs about such things as location, registration for services, traffic direction, radio network services, and available bandwidth.
I’ve been alarmed by the slow progress of Debian towards the next release. They’ve had several weird gyrations in numbers of “release-critical” bugs and still many packages fail to build from source. Last time this stage, they had only a few hundred bugs to go. Now they are over 600. I guess some of that comes from increasing the number of included packages. There are bound to be more bad interactions, like changing the C compiler. I hate that language which seems to be a moving target… Systemd seems to be smoother but it still gives me problems.
2016 was a good year for Mir – it is being used in more places, it has more and better upstream support and it is easier to use by downstream projects. 2017 will be even better and will see version 1.0 released.
Almost every new major feature people have been asking us for, be it high bit depth support, or full CMYK support, or layer effects, would be impossible without having a robust, capable image processing core.
Øyvind Kolås picked up GEGL in mid-2000s and has been working on it in his spare time ever since. He is the author of 42% of commits in GEGL and 50% of commits in babl (pixel data conversion library).
When we released GIMP 2.9.2 in late 2015 and stepped over into 2016, we already knew that we’d be doing mostly polishing. This turned out to be true to a larger extent, and most of the work we did was under-the-hood changes.
But quite a few new features slipped in. So, what are the big user-visible changes for GIMP in 2016?
Dart already has an excellent virtual machine which uses just-in-time compilation to get excellent performance. Since Dart is dynamically typed (more precisely, it’s optionally typed), a JIT compiler is a natural fit — it can use the types available at runtime to perform optimizations that a static compiler can’t do.
In our recent article, we talked about Exercism, an open source project to help people level up in their programming skills with exercises for dozens of different programming languages. Practitioners complete each exercise and then receive feedback on their response, enabling them to learn from their peer group's experience.
Katrina Owen is the founder of Exercism, and I interviewed her as research for the original article. There are some fantastic nuggets of information and insight in here that we wanted to share with anyone interested in learning to programming, teaching programming, and how a project like this takes contributions like this from others.
The phrase “You are Not Expected to Understand This” is probably the most famous comment in the history of Unix.
And last month, at the Systems We Love conference in San Francisco, systems researcher Arun Thomas explained to an audience exactly what it was that they weren’t supposed to understand.