Efficiently execute 100K update statements - C# & Sql Server -

my c# application retrieves on million records sql server, processes them , updates database back. results in close 100,000 update statements , have following form -

update table1 set col1 = <some number> id in (n1, n2, n3....upto n200) 

"id" int, primary key clustered index. no 2 update statements update same ids, in theory, can run in parallel without locks. therefore, ideally, suppose should run many possible in parallel. expectation finish in no more 5 minutes.

now, question efficient way of doing it? i'm trying below -

1. running them sequentially 1 one - least efficient solution. takes on hour.
2. running them in parallel launching each update in it's on thread - again inefficient because we're creating thousands of threads tried anyway , took on hour , quite few of them failed because of or connection issue.
3. bulk inserting in new table , join update. run concurrency issues because more 1 user expected doing it.
4. merge batches instead of updates - google says merge slower individual update statements haven't tried it.

i suppose must common problem many applications out there handle sizeable amounts of data. there standard solutions? ideas or suggestions appreciated.

i created integer tbl type can pass id's sp list , single query update whole table.

this still slow see way more quicker conventional "where id in (1,2,3)"

definition type

create type [dbo].[integer_list_tbltype] table(     [n] [int] not null,     primary key clustered  (     [n] asc )with (ignore_dup_key = off) ) go 

here usage.

declare @intval integer_list_tbltype declare @colval int=10  update c set c.col1=@colval @intval join table1 c on c.id = i.n 

let me know if have questions.