E2E: Erik Meijer and Burton Smith - Concurrency, Parallelism and Programming

Actually, it's quite obvious. C#, Java, C++, C are sugar coated assembler. Reasoning about assembler, even sugar coated is a lost cause. Making those languages into something that can be reasoned about at compile and especially run-time would be practically impossible because of long hairy legacy that those languages carry around.

In order to run a program on a parallel hardware, run-time would have to reason about side effects to come up with some strategy to partition computational graph into work loads that have minimal interactions between each other.

If many core processors will have cores of different capabilities (which seems to be the case), run-time reasoning and JIT will be a necessity.

It seems like none of the existing imperative languages would survive transition to parallel era. Of course run-times are still be written in something that is sugar coated assembly, yet for general-purpose programming completely new languages would be required.

Declarative and richly typed presumably.

Also to the point of run-time reasoning and code generation, to provide fault tolerance computational graph might need to be re-evaluated if a computation node returns exceptional value or goes into non-termination state. That in theory would allow automatic remediation for run-away queries in databases and handling of non-responding services in the cloud (as well as mutating hardware - failed or hot plugged general and special purpose CPUs, failed or hot plugged memory and so on).

It probably will take another 10 to 20 years to get it right, but it looks like that's where things are going.

Right, and old ideas are just facades on even older ideas and so on recursively till the big bang

In the end it will be about believes, whether one believe this or that language being "new" or not. Attempts to define "pure novelty" would end up nowhere.

On the subject of strict or linient evaluation.

It seems that an adanced enough run-time can and should use both, based on the accumulated "knowledge" (stats) about workloads being executed.

Expectation that something can be strictly evaluated in false in absolute sense, because each and every CPU instruction and/or memory read/write may fail because of faulty hardware. Yet, it can be statistically true. If hardware is somehow known to be 99.something% reliable, such assumption can be made safely (in statistical sense), otherwise nothing can be computed or done ever.

(I believe that proponents of strict evaluation are stuck because they base their reasoning on incorrect assumptions without explicitly stating what those assumptions are, which is a known issue that plagued physics for centuries, and most likely still does)

The same must apply to the algorithms as well. If algorithm is known to be predictable on a given workload (either statistically or by devine intervention of the mister human), it's OK to evaluate is strictly. If there is no prior knowledge, lazy evaluation is the way to go and please gather execution stats upon exit so it can be reused in the future evaluations/executions. And if it does not exit in the requested amount of time - abandon (preferrably kill first) the execution and and black list it (till the end of time or the next devine intervention).

From 10000 feet it looks like a nice logical schema with a feed back loop, which is statistically a necessity for each and every successful eco system (observe the nature).