# Ebay server vs home constructed ONLY for julia coding

**URL:** https://discourse.julialang.org/t/ebay-server-vs-home-constructed-only-for-julia-coding/70044
**Category:** Offtopic
**Created:** [October 19, 2021, 3:43pm UTC](https://discourse.julialang.org/t/ebay-server-vs-home-constructed-only-for-julia-coding/70044 "2021-10-19T15:43:08Z")
**Posts on this page:** 1
**Showing post:** 8

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### Author: ![ImreSamu](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/imresamu/32/20677_2.png) [@ImreSamu](https://discourse.julialang.org/u/ImreSamu)
#### Post date: [October 19, 2021, 7:00pm UTC](https://discourse.julialang.org/t/ebay-server-vs-home-constructed-only-for-julia-coding/70044/8 "2021-10-19T19:00:34Z")

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> [@anon69491625](#):
>
> EVERY laptop I have ever owned ( except my fav x1 carbon gen 3) has been a disaster. I do see your point though.

other alternative: [https://frame.work/](https://frame.work/) laptops

- DIY friendly Linux compatibility; max 2x32GB RAM ; i5-i7 11gen + AVX512; + [SN850 is the fastest Gen4 SSD](https://www.anandtech.com/print/16505/the-western-digital-wd-black-sn850-ssd-review)
  - [https://news.ycombinator.com/item?id=28849220](https://news.ycombinator.com/item?id=28849220)
    - —\> [https://frame.work/marketplace](https://frame.work/marketplace)

  - [https://news.ycombinator.com/item?id=27926425](https://news.ycombinator.com/item?id=27926425)
  - [https://news.ycombinator.com/item?id=26263508](https://news.ycombinator.com/item?id=26263508)

it is not nVidia CUDA; but you can test the Intel oneAPI solution

- [GitHub - JuliaGPU/oneAPI.jl: Julia support for the oneAPI programming toolkit.](https://github.com/JuliaGPU/oneAPI.jl)

> [@anon69491625](#):
>
> , I meant 20 - 30gb of data. No doubt this will, like a gas, expand to fill the available memory.

Sometimes I am processing [a ~100GB compressed Wikidata JSON DUMP](https://dumps.wikimedia.org/wikidatawiki/entities/) or OpenStreetMap dump on my laptop  
( 24GB RAM + 1TB SSD + 8gen Intel CPU - Thinkpad T480s )  
My method: extreme prefiltering → loading the minimal data to SQL database (PostgreSQL)  
( in my case this is geodata - so [PostGIS](https://postgis.net/) is a must )

IMHO: with sqlite/postgreSQL/mySQL you can handle data larger than fits into RAM

And with PostgreSQL - you can use Julia as an embedded - procedural language

- [pljulia / pljulia · GitLab](https://gitlab.com/pljulia/pljulia) ( … work in progress )

in the next year: you can expect laptops with 12c - 16c Intel mobil CPU-s - so no easy decision.

- [Intel Core i9-12900H high-end laptop CPU spotted with 14 cores and 20 threads - VideoCardz.com](https://videocardz.com/newz/intel-core-i9-12900h-high-end-laptop-cpu-spotted-with-14-cores-and-20-threads) ( only AVX2 )

+info: [Dataframes.jl #1 requests: “handling data larger than fits into RAM”](https://discourse.julialang.org/t/future-directions-for-dataframes-jl/66247/1)

> 2 Xeon E5-2699 v3 therefore 2 \* 18 core and 2 \* 36 threads.

other important: you can expect extremely low single-core performance;  
and not all Julia package is optimized for multithreading.

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