“Tutanota is the end-to-end encrypted mail client that enables you to communicate securely with anyone…”
“NGINX release 1.9.1 introduces a new feature that enables use of the SO_REUSEPORT socket option, which is available in newer versions of many operating systems, including DragonFly BSD and Linux (kernel version 3.9 and later). This option allows multiple sockets to listen on the same IP address and port combination. The kernel then load balances incoming connections across the sockets, effectively sharding the socket.
(For NGINX Plus customers, this feature will be available in Release 7, which is scheduled for later this year.)
The SO_REUSEPORT socket option has many real-world applications, such as the potential for easy rolling upgrades of services. For NGINX, it improves performance by more evenly distributing connections across workers…”
From C to Go
gc tool chain has been converted from C to Go.
compile tool replaces
link tool replaces
asm tool replaces
Go 1.5 has no C code in the tool chain or runtime.
Rob will talk more about this.
Go in Go
As of the 1.5 release of Go, the entire system is now written in Go.
(And a little assembler.)
C is gone.
gccgo is still going strong.
This talk is about the original compiler,
“Now that Rust 1.0 is out and quite stable, I thought it might be interesting to write an introduction to Rust for Python programmers. This guide goes over the basics of the language and compares different constructs and how they behave.
Rust language wise is a completely different beast compared to Python. Not just because one is a compiled language and the other one is interpreted, but also because the principles that go into them are completely different. However as different as the languages might be at the core, they share a lot in regards to ideas for how APIs should work. As a Python programmer a lot of concepts should feel very familiar…”
“Pregel: A System for Large-Scale Graph Processing – Malewicz et al. (Google) 2010
“Many practical computing problems concern large graphs.”
Yesterday we looked at some of the models for understanding networks and graphs. Today’s paper focuses on processing of graphs, especially the efficient processing of large graphs where large can mean billions of vertices and trillions of edges. Pregel is the system at Google that powers PageRank, which makes it a very interesting system to study. It is also the inspiration for Apache Giraph, which Facebook use to analyze their social graph.
There are single machine-sized graph processing problems, and then there are distributed graph processing problems. You probably don’t want to be using a distributed graph processing platform to solve a problem that would fit on one machine (See Musketeer), but if you really do have a large graph, then…”
“Lush is an object-oriented programming language designed for researchers, experimenters, and engineers interested in large-scale numerical and graphic applications. Lush is designed to be used in situations where one would want to combine the flexibility of a high-level, weakly-typed interpreted language, with the efficiency of a strongly-typed, natively-compiled language, and with the easy integration of code written in C, C++, or other languages.
Lush is Free Software (under the GPL license) and runs on GNU/Linux, Solaris, Irix, and Windows under Cygwin.
Lush can be used advantageously for projects where one would otherwise use a combination of an interpreted language like Matlab, Python, Perl, S+, or even (gasp!) BASIC, and a compiled language like C. Lush brings the best of both worlds by wrapping three languages into one: (1) a weakly-typed, garbage-collected, dynamically scoped, interpreted language with a simple Lisp-like syntax, (2) a strongly-typed, lexically-scoped compiled language that uses the same Lisp-like syntax, and (3) the C language, which can be freely mixed with Lush code within a single program, even within a single function. It sounds complicated, but it is not. In fact, Lush is designed to be very simple to learn and easy to use.
If you do research and development in signal processing, image processing, machine learning, computer vision, bio-informatics, data mining, statistics, simulation, optimization, or artificial intelligence, and feel limited by Matlab and other existing tools, Lush is for you. If you want a simple environment to experiment with graphics, video, and sounds, Lush is for you…”