chancho

http://www.boost.org/doc/libs/1_47_0/doc/html/intrusive.html

Not that most of what you said isn't true. Just picking the nit that 'the container owns the data' holds only for the STL, not C++ in general.

It generalizes the choice of 0 or 1 to an arbitrary starting index. So when you create an array you specify not just where it ends but also where it begins. This lets you do neat things (consider a filter kernel with range [-s,+s]^n instead of [1,2s]^n) and the extra complexity it adds can be hidden when not needed using for-statements or higher order functions.

Nobody uses it because the implementation is not very efficient and Haskellers have a chip on their shoulder about performance. It subtracts the origin and computes strides on every index, but you could easily avoid this by storing the subtracted base pointer and strides with the array. Of course when you go to implement it you'll see light on 0-based indexing :)

In particular, the key feature of C++ templates (as opposed to other similar systems of polymorphism) is that they abstract over not just code but data representation. This is what CJefferson was getting at and it's orthogonal to macros. Ocaml and Scala don't offer it. It's about data, not code, so you'll never be able to gloss over it with extra parallelism.

In C++ a std::pair<double,double> really is just two doubles, 16 bytes. It can be passed into and returned from functions in registers. If I have a singly-linked list of them, each list cell is 24 bytes (16 for the pair, 8 for the next pointer.) In any other (mainstream) language, the pair is really a pair of pointers to boxed doubles which reside in the heap, and the list cell holds a pointer to that. The overhead of this is unacceptable in many situations, and these situations are where C++ still thrives. (cf. the Eigen linear algebra library for an example of "doing it right.")

Most languages have given up on this feature because of the drawbacks (code bloat) and the unified runtime representation of data (basically everything is a void*) makes many things easier (garbage collection, serialization, etc.) (I'm not super familiar with C# but I understand the struct types address this somewhat, but not without their own drawbacks.) But thanks to LLVM (written in C++ btw) people are pushing this area of language development forward (Rust, Deca, and others) in an attempt to fix the (many) problems of C++ while preserving its strengths.

Oh and BTW: A tank with wings is called an A-10 warthog :)

But it's still hard to know what people want or need to buy right now

They can (and do) personalize it somewhat, but just aren't as well-placed as facebook, because they aren't as close to the user (people). People are ultimately where the money comes from. That's how advertisers get it.

So who's information is more valuable? Facebook's because they know more about you overall (your friends, your habits etc.) or Google's because they know what you want right now (because you just entered it right fucking there in the search box)

I'm leaning toward Google. If someone has a problem, they go to Google to search for ways to solve it, and as you point out, that's precisely when they're most amenable to advertising. People go to Facebook to connect with other people. Advertising will always be noise there. (Stupid mindless games notwithstanding.)

Does anyone know the rationale for this? If they had used 64 bit long values, like the underlying OS calls, his whole matrix could have been mapped into a single buffer, making all this list-of-mappings stuff unnecessary. That extra level of indirection normally wouldn't matter much but in this case he's paying the cost 1e12 times over.

Is this conventional wisdom? How does a petaflop race affect app servers and databases? It seems like most traditional server workloads could get by without a single FPU. The only thing they have in common is IO. Are there many data centers using Infiniband? (Maybe there are I don't know.)

The Cell architecture is an evolutionary dead end. SPARC is no more of a threat to X86 now than before. GPUs may be the next big thing for HPC but its got a long way to go to get out of its niche in the server market. (That niche being... face detection for photo sharing sites? Black-Scholes? Help me out here.)

I mean, I agree with your overall point, but I think it's more likely that ARM will steal all the data center work before anything from the HPC world does. They are too focused on LINPACK.

http://www.babynamewizard.com/voyager#

They aren't just using it to drive ad traffic and promote the book, but are now (since I last looked) actually charging for the visualizations themselves. And presumably people are paying, but who knows...

On the plus side, this means there's a market, but you've got a long way to go to catch them, both in regards to the visualizations and the breadth of the name database. It's a good start, though.

If instead you use 1 <= i <= (NxM), 1 <= row <= M, 1 <= col <= N, then the mappings aren't nearly as clean. Sure, you could hide all this behind some kind of API, eg. Image.getPixel(x,y), but if you work with multidimensional arrays very often, eventually you'll need to marshal arrays back and forth between different containers that use different access APIs, and the simplest common representation to use for this kind of data is as a 1D array, so being able to work with nD data that is stored in a 1D array comes up fairly often.

Nope. This is what dilettantes call them. Capable C++ programmers (I don't claim to be a master, that would be foolish) know how to grep the standard. The term "functor" is not found in it, at least not that draft that comes up first on Google. The plain and transparent term "function object" has its own section, 20.3.

What is an example of an optimization that a JIT compiler can make that a AOT compiler cannot?

If the developer is able to profile the application on typical end-user workloads, don't profile-guided optimizations provide the same benefit as JIT runtime profiling?

Why can't an AOT compiler just consider every path a "hot" path?

Last but not least: Got any benchmarks?

Can't speak for other fields, but in CS any outlet worth submitting to will let you post a preprint on your own website, and from there Google Scholar will pick it up and place the link to your free copy right next to the paywall link. It's not a perfect system---it's like an extreme form price discrimination, like when Microsoft turns a blind eye to piracy in emerging markets---but it does give access to those who can't pay, and its not as dystopian as you make it out to be.

So peer reviewed journals are only important for grants, but your community doesn't rely on peer reviewed journals. Do you not rely on grants? Who funds your work? Do you all work for free, in your spare time?