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Distributed Powerset


Distributed Powerset

By : ChadR
Date : November 22 2020, 02:59 PM
help you fix your problem If you use n bits of an integer to represent the items in a subset of n items, you can start the variable at 0, and increment it to get to the next subset. So to evenly distribute the work between k processors, you can simply have processor #i start its integer variable at i and add k to it on each step. Every subset will be processed by exactly one processor.
Bear in mind that this won't do very much to help you solve large problems. If you can solve a problem of size x on a single computer (and I'd estimate 20 <= x <= 30 on today's computers, roughly), then even by buying 1024 computers you would only be able to solve a problem of size x+10.
code :


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What are the advantages of a distributed version control for a team that is effectively never distributed?

What are the advantages of a distributed version control for a team that is effectively never distributed?


By : user2030751
Date : March 29 2020, 07:55 AM
help you fix your problem I would recommend HgInit as a very thorough explanation of just how svn is improved upon by a decentralized toolset. It will also help you to understand the conceptual differences.
One of the big improvements I'd like to emphasize is the notion of merge tracking. Subversion didn't have this feature at all until 1.5, and with the difference in the way it treats revisions and branches, it will probably never be as good as the decentralized tools can be. Nobody likes merges. Might as well reduce as much of that pain as you can. Also see: Why is branching and merging easier in Mercurial than in Subversion?.
Framework for distributed computing for .Net / Mono that supports persistence of distributed tasks

Framework for distributed computing for .Net / Mono that supports persistence of distributed tasks


By : user2106285
Date : March 29 2020, 07:55 AM
Does that help Have you looked at the Microsoft DSS / CCR framework? It's a SOA, Concurrent framework initially developed on the robotics platform. We previously used it to create a traffic simulator. It's not open per-se but its not to expensive, and I believe free for academia.
You would have to write the logic to create parallel jobs, but this in theory should not be to difficult. The framework has a bunch of management tools.
How are Distributed Snapshot algorithms (likes of Chandy Lamport) implemented in real world Distributed systems?

How are Distributed Snapshot algorithms (likes of Chandy Lamport) implemented in real world Distributed systems?


By : user2471633
Date : March 29 2020, 07:55 AM
hope this fix your issue It can be useful for rollback recovery systems on network-on-chip (NOC) systems.It is also used for determining the global state of the system during computation.
As an example HP uses this kind of algorithms for rollback-recovery protocol for crash/recover hosts and fair-loss links. you can find an interesting article about that here:
MySql: Evenly distributed sample size on unevenly distributed data

MySql: Evenly distributed sample size on unevenly distributed data


By : Holger Bartel
Date : March 29 2020, 07:55 AM
wish helps you You can use union for that with a limit on each sub select:
code :
(SELECT * FROM profiles WHERE People_amount=1 LIMIT 333)
UNION
(SELECT * FROM profiles WHERE People_amount=2 LIMIT 333)
UNION
(SELECT * FROM profiles WHERE People_amount=3 LIMIT 333)
select     p.*
from       (
            select   people_amount,  
                     count(*) as occurrences
            from     profiles
            group by people_amount) as stats
inner join profiles p
        on p.people_amount = stats.people_amount         
order by   rand() * stats.occurrences
limit      1000
select     p.*
from       (
            select   people_amount,  
                     destination,
                     count(*) as occurrences
            from     profiles
            group by people_amount,
                     destination) as stats
inner join profiles p
        on p.people_amount = stats.people_amount         
       and p.destination = stats.destination
order by   rand() * stats.occurrences
limit      1000
How to make a regression line in R using a normally distributed error and a uniformly distributed random variable

How to make a regression line in R using a normally distributed error and a uniformly distributed random variable


By : user3261295
Date : March 29 2020, 07:55 AM
wish of those help Arithmetic operators in R work on vectors, so you don't need the loops at all:
code :
y <- 5 + 3 * xvals + evals
xvals <- runif(n = 100, min = -1, max = 1)
evals <- rnorm(n = 100, mean = 0, sd = 1)
y <- 5 + 3 * xvals + evals

print(y)
plot(xvals, y)
y <- append(y, 5 + 3*x + e)
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