C++17 Structured Bindings--Steve Lorimer
C++17 Structured Bindings
by Steve Lorimer
From the article:
Introduced under proposal P0144R0, Structured Bindings give us the ability to declare multiple variables initialised from a
tupleorstruct.
CppCon 2015 Racing The File System--Niall Douglas
Have you registered for CppCon 2016 in September? Don’t delay – Registration is open now.
While we wait for this year’s event, we’re featuring videos of some of the 100+ talks from CppCon 2015 for you to enjoy. Here is today’s feature:
Racing The File System
by Niall Douglas
Summary of the talk:
Almost every programmer knows about and fears race conditions on memory where one strand of execution may concurrently update data in use by another strand of execution, leading to an inconsistent and usually dangerous inconsistent read of program state. Almost every programmer therefore is aware of mutexes, memory ordering, semaphores and the other techniques used to serialise access to memory.
Interestingly, most programmers are but vaguely aware of potential race conditions on the filing system, and as a result write code which assumes that the filing system does not suddenly change out from underneath you when you are working on it. This assumption of a static filing system introduces many potential security bugs never mind ways of crashing your program, and of course creating data loss and corruption.
This workshop will cover some of the ways in which filing system races can confound, and what portable idioms and patterns you should employ to prevent misoperation, even across networked Samba shares. Finally, an introduction of the proposed Boost library AFIO will be made which can help application developers writing filing system race free code portably.
CppChat 2015-08-21: Jason Turner and Matt Bentley
Video chat:
CppChat 08-21 with Jason and Matt
with Jason Turner, Matt Bentley, and Jon Kalb
From the chat:
We discuss CppCon sessions including Matt's session on the game-friendly containers that he has created and Jason's plenary talk about writing a game for Commodore 64 in C++17, the reprisal of his award-winning C++Now talk on "Practical Performance Practices," and his talk with Rob Irving on their CppCast experiences. Along the way we discuss the history of the 6502 and Stepanov's observation that the STL was not designed with today's hardware in mind.
CppChat 2015-08-14 boost and C++ Standard -- Jon Kalb
Video chat:
CppChat 2016-08-14 with Matt and Robert
with Matt Calabrese, Robert Ramey, and Jon Kalb
From the chat:
We discuss Boost, the Boost Incubator, the review process, and the role of Boost in standardization.
How Bloomberg is Advancing C++ at Scale--John Lakos
Interesting interview:
How Bloomberg is Advancing C++ at Scale
by John Lakos
From the article:
John Lakos manages the Bloomberg Development Environment group, which offers a set of C++ software libraries, development tools, and methodology to well over a thousand Bloomberg developers. He is an authority on large-scale C++ software infrastructure, receiving recent acclaim for two publications by Pearson Education on methodology for industrial software development [Part 1, Part 2]. BDE and its libraries are open source and can be found on GitHub. In this conversation, Lakos discusses the importance of instilling process and discipline in all software development projects...
CppCon 2015 C++ Rcpp: Seamless R and C++ Integration--Matt P. Dziubinski
Have you registered for CppCon 2016 in September? Don’t delay – Registration is open now.
While we wait for this year’s event, we’re featuring videos of some of the 100+ talks from CppCon 2015 for you to enjoy. Here is today’s feature:
Rcpp: Seamless R and C++ Integration
by Matt P. Dziubinski
Summary of the talk:
R is an open-source statistical language designed with a focus on data analysis. While its historical roots are in statistical applications, it is currently experiencing a rapid growth in popularity in all fields where data matters: from data science, through bioinformatics and finance, to machine learning. Key strengths contributing to this growth include its rich libraries ecosystem (over 6 thousands packages at the moment of writing) – often authored by the leading researchers in the field, providing early access to the latest techniques; beautiful, high-quality visualizations – supporting seamless exploratory data analysis and producing stunning presentations; all of this available in an interactive environment resulting in high productivity through fast iteration times.
At the same time, there are no free lunches in programming: the dynamic, interactive nature of R does have its costs, including a significant impact on run-time performance. In an era of growing data sizes and increasingly realistic models this concern is only becoming more important.
In this talk we provide an introduction to Rcpp – a library allowing smooth integration of R with C++, combining the productivity benefits of R for data science together with the performance of C++. First released in 2005, today it’s the most popular language extension for R -- used by over 400 packages. We'll also discuss challenges (as well as possible solutions) involved in integrating modern C++ code, and demonstrate the usage of popular C++ libraries in practice. We’ll conclude the talk with the RInside package allowing to embed R in C++.
CppCon 2015 C++ on the Web: Ponies for developers without pwn’ing users--JF Bastien
Have you registered for CppCon 2016 in September? Don’t delay – Registration is open now.
While we wait for this year’s event, we’re featuring videos of some of the 100+ talks from CppCon 2015 for you to enjoy. Here is today’s feature:
C++ on the Web: Ponies for developers without pwn’ing users
by JF Bastien
Summary of the talk:
Is it possible to write apps in C++ that run in the browser with native code speed? Yes. Can you do this without the security problems associated with running native code downloaded from the net? Yes and yes. Come to this session to learn how.
We'll showcase some resource-intensive applications that have been compiled to run in the browser. These applications run as fast as native code with access to cornerstone native programming APIs—modern C++ STL, OpenGL, files and processes with full access to C++’s concurrency and parallelism—all in an architecture- and OS-agnostic packaging. Then, we'll describe how we deliver native code on the web securely, so developers get their C++ ponies and users don’t get pwn’d. We’ll also touch on the fuzzing, code randomization, and sandboxing that keep the billions of web users safe.
C++ Weekly Episode 24: C++17’s Structured Bindings—Jason Turner
Episode 24 of C++ Weekly.
C++17's Structured Bindings
by Jason Turner
About the show:
In this episode Jason introduces C++17's structured bindings.
Quick Q: Efficiency of postincrement v.s. preincrement in C++
Quick A: The difference is only marginal with optimizations enabled.
Recently on SO:
Efficiency of postincrement v.s. preincrement in C++
It is true - although perhaps overly strict. Pre increment doesn't necessarily introduce a data dependency - but it can.
A trivial example for exposition:
a = b++ * 2;Here, the increment can be executed in parallel with the multiplication. The operands of both the increment and the multiplication are immediately available and do not depend on the result of either operation.
Another example:
a = ++b * 2;Here, the multiplication must be executed after the increment, because one of the operands of the multiplication depends on the result of the increment.
Of course, these statements do slightly different things, so the compiler might not always be able to transform the program from one form to the other while keeping the semantics the same - which is why using the post increment might make a slight difference in performance.
A practical example, using a loop:
for(int i= 0; arr[i++];) count++; for(int i=-1; arr[++i];) count++;One might think that the latter is necessarily faster if they reason that "post-increment makes a copy" - which would have been very true in the case of non-fundamental types. However, due to the data dependency (and because int is a fundamental type with no overload function for increment operators), the former can theoretically be more efficient. Whether it is depends on the cpu architecture, and the ability of the optimizer.
For what it's worth - in a trivial program, on x86 arch, using g++ compiler with optimization enabled, the above loops had identical assembly output, so they are perfectly equivalent in that case.
Rules of thumb:
If the counter is a fundamental type and the result of increment is not used, then it makes no difference whether you use post/pre increment.
If the counter is not a fundamental type and the result of the increment is not used and optimizations are disabled, then pre increment may be more efficient. With optimizations enabled, there is no difference.
If the counter is a fundamental type and the result of increment is used, then post increment can theoretically be marginally more efficient - in some cpu architecture - in some context - using some compiler.
If the counter is a complex type and the result of the increment is used, then pre increment is typically faster than post increment. Also see R Sahu's answer regarding this case.
CppCon 2015 std::allocator Is to Allocation what std::vector Is to Vexation--Andrei Alexandrescu
Have you registered for CppCon 2016 in September? Don’t delay – Registration is open now.
While we wait for this year’s event, we’re featuring videos of some of the 100+ talks from CppCon 2015 for you to enjoy. Here is today’s feature:
std::allocator Is to Allocation what std::vector Is to Vexation
by Andrei Alexandrescu
Summary of the talk:
std::allocator has an inglorious past, murky present, and cheerless future. STL introduced allocators as a stop gap for the now antiquated segmented memory models of the 1990s. Their design was limited and in many ways wasn't even aiming at helping allocation that much. Because allocators were there, they simply continued being there, up to the point they became impossible to either uproot or make work, in spite of valiant effort spent by the community.
But this talk aims at spending less time on poking criticism at std::allocator and more on actually defining allocator APIs that work.
Scalable, high-performance memory allocation is a topic of increasing importance in today's demanding applications. For such, std::allocator simply doesn't work. This talk discusses the full design of a memory allocator created from first principles. It is generic, componentized, and composable for supporting application-specific allocation patterns.