neuromantik8086

I never answered your last question so here goes:

> Are you saying that the reproductive challenge poses a difficulty to Common Workflow Language?

I don't actually understand how the reproducibility challenge undermines the validity of using CWL / flow-based programming as an approach to promoting reproducible analyses. There certainly wasn't anything in the article that made me think that CWL was challenged, but Hinsen explicitly called out CWL in the abstract, which implies that for some reason he thinks, a priori, that it's a non-solution. He never justifies this implied assumption further, and as near as I can tell, none of the attempted replications used a flow-based language.

If Hinsen really aimed to argue against the viability of CWL/flow-based programming as an approach to reproducibility, he would have done a systematic comparison of historical analyses that used a flow-based system (like National Instruments' Labview or Prograph) vs analyses that are more similar to the approach that he seems to favor (i.e., analyses using Mathematica or Maple).

While I find the challenge interesting to follow, and the retrocomputing geek in me finds it fun, I don't actually understand what it really accomplished other than being a fun diversion. Assuming that an analysis was written in a Turing-complete language and you didn't use non-deterministic algorithms, you should theoretically be able to reproduce the results exactly on modern hardware, and using non-deterministic algorithms I would imagine that a result would be "close enough" within some kind of confidence interval. You may need to go to great lengths (in terms of emulating instruction sets, ripping tapes, etc), but I think a visit to any retrocomputing festival or computer history museum would have made that pretty obvious from the outset.

I can only speak to Spack in particular, but the main issue that I found with it was balancing researcher expectations for package installation speed with compile times. For most packages, compile times aren't a huge problem, but compilers themselves can take days to build, and it isn't unheard of for researchers to want a recent version of gcc for some of their environments.

In theory this isn't an issue with Spack (assuming that you have a largely homogeneous set of hardware or don't use CPU family-specific instruction sets), since you can set up cached, pre-compiled binaries on a mirror server (similar to a yum repo) and have people install from there.

Spack, however, has a lot of power/complexity. A lot of untamed power that means that bugs can sometimes be more likely than in other, more mature (or mature-ish) package managers. Namely, Spack allows you to not only specify the version number of a package, but also the compiler that you use to make that package, specific versions of dependencies that you want to use, which implementation of an API you want to use (i.e., MPICH or OpenMPI for MPI), and compiler flags for that package. When you run an install command / specify what you want to install, Spack then performs dependency resolution and "concretizes" a DAG that fulfills all of the constraints.

The issue that I ran into was that if you don't specify everything, Spack makes decisions for you about which version of a dependency, which compiler, etc to use (i.e., it fills in free variables in a space with a lot of dimensions). This would be great and dandy normally, although the version of Spack that I used occasionally constructed totally different graphs for the same "spack install gcc" command (if I recall correctly; take all of this with a grain of salt b/c I might be misremembering). This meant that it wouldn't use cached versions of gcc that had already been built, and ended up rebuilding minor variants of gcc with options I didn't care about.

At National Labs and larger outfits, the trade-offs between this kind of complexity/power and the accompanying bugginess (Spack has yet to hit 1.0) seem to favor complexity/power while accepting these sorts of bugs, but I don't work at a larger outfit and my group didn't need that level of power/control over dependencies and rather needed something that "just worked" and would allow researchers to be able to install packages independently of us (IT people). conda (mostly) fit the bill for this. I still think that Spack is the future and it has a special place in my heart, but it will have to be more stable for me to want to use it in production.

I never said that Konrad Hinsen's agenda was hidden; in fact, it's not at all hidden (which is why I linked the abstract). It's just that this context isn't at all clear in the Nature write-up, and it's relevant to take into account.

I haven't taken the time to seriously contemplate the merits of CWL vs Leibniz, although my gut instinct is that we don't really need another domain-specific language for science given the profusion of such languages that already exist (Mathematica, Maple, R, MATLAB, etc). That's the extent of my bias, but again, it's a gut instinct and not a comprehensive well-reasoned argument against Leibniz.

The COO majored in Music Technology at Oberlin. That's quite a bit more technical than most people realize. TIMARA (the music tech program at the Oberlin Conservatory) involves a decent amount of programming and/or audio engineering. To put that in perspective, the founder of Macromind/Macromedia (Marc Canter) is also an alumnus of TIMARA.

Modern services such as reddit and Twitter effectively usurp the role that Usenet/NNTP and similar distributed protocols used to fulfill, but without the advantage of decentralization / lack of large single points of failure that such protocols embraced. That's what I was getting at, and maybe I'm full of shit.

In the 80s if a university campus internet connection went down, only that university was affected. Now, when a single AWS availability zone goes down, a much wider swath of users is impacted. Such consolidation / centralization shows a disregard for the spirit of the early internet and design considerations that went into it.

Again, maybe I'm full of shit. Lots of people here seem to think so.

We wouldn't have this problem if people just used application-layer protocols and federated services like the early internet.

Resource Public Key Infrastructure, but ISPs are too cheap to actually implement it.

Maybe I'm being obtuse, but doesn't using a configuration management tool to deploy black-box Docker containers eliminate many of the advantages of using config management in the first place?

I mean, part of the appeal of the Louvre at least isn't just that you can see the art in the physical world, but that you're practically bathed in it. This sense of being overwhelmed and the serendipity factor in discovering new works constituted a lot of the appeal when I used to visit there. You could go into there once every weekend for a year and never have the same experience twice.