outcome | lightweight outcome < T > and result < T > ( non-Boost edition | SDK library

Here's a way using separate_rows:

Taking advantage of numpy broadcasting, you can do it easily:

Synthesizing some of the comments here...

?`[` says:

Unlike S (Becker et al p. 358), R never uses partial matching when extracting by [, and partial matching is not by default used by [[ (see argument exact).

But ?`[.data.frame` says:

Both [ and [[ extraction methods partially match row names. By default neither partially match column names, but [[ will if exact = FALSE (and with a warning if exact = NA). If you want to exact matching on row names use match, as in the examples.

The example given there is:

Just quick speedups:

1. You can omit math.sqrt()
2. Create dictionary of colors instead of a list (that way you don't have to search for the index each iteration)
3. use min() instead of sorted()

You may try

I assume, given when you posted this question, you are using LTS 18.17. Looking at that LTS, it uses mintty 0.1.3. Looking in mintty 0.1.3's cabal file shows a special flag that is enabled by default that means that System.Console.MinTTY.Win32 is not included. The comments in that cabal file say that that flag should be used when using Win32 2.13.1.0 or newer.

However, when I look at LTS 18's configuration in Stackage, I can see that it is using Win32 2.6.2.1, so that flag ought to be set to false for this package to work.

So let's check that in the Stackage build constraints. I see that another flag is being set, and it seems to be an old flag that is no longer used (looks like it was used in an older 0.1.2 version). This must be the problem.

The solution: manually set the flag in your stack.yaml:

So the solution is quiet simple. All I had to do is using a Webpack plugin. The best Plugin to fit this task is NormalModuleReplacementPlugin which is provided out of the box by Webpack itself.

The exclude in tsconfig.ts is no longer reasonable within this solution.

Simply provide the following plugin:

dplyr developers recommend rbindlist() for this apparently: https://github.com/tidyverse/dplyr/issues/1162

The TLDR is that loads which miss all levels of the TLB (and so require a page walk) and which are separated by address unknown stores can't execute in parallel, i.e., the loads are serialized and the memory level parallelism (MLP) factor is capped at 1. Effectively, the stores fence the loads, much as lfence would.

The slow version of your insert function results in this scenario, while the other two don't (the store address is known). For large region sizes the memory access pattern dominates, and the performance is almost directly related to the MLP: the fast versions can overlap load misses and get an MLP of about 3, resulting in a 3x speedup (and the narrower reproduction case we discuss below can show more than a 10x difference on Skylake).

The underlying reason seems to be that the Skylake processor tries to maintain page-table coherence, which is not required by the specification but can work around bugs in software.

For those who are interested, we'll dig into the details of what's going on.

I could reproduce the problem immediately on my Skylake i7-6700HQ machine, and by stripping out extraneous parts we can reduce the original hash insert benchmark to this simple loop, which exhibits the same issue: