{"id":122176,"date":"2026-10-08T12:30:00","date_gmt":"2026-10-08T10:30:00","guid":{"rendered":"https:\/\/aixia.se\/gpu-computing-in-the-nordic-region-where-should-the-ai-infrastructure-be-located\/"},"modified":"2026-10-08T12:30:00","modified_gmt":"2026-10-08T10:30:00","slug":"gpu-computing-in-the-nordic-region-where-should-the-ai-infrastructure-be-located","status":"publish","type":"post","link":"https:\/\/aixia.se\/en\/gpu-computing-in-the-nordic-region-where-should-the-ai-infrastructure-be-located\/","title":{"rendered":"GPU Computing in the Nordic Region: Where Should the AI Infrastructure Be Located?"},"content":{"rendered":"<style>.aixia-post{color:#1f2933;font-size:17px;line-height:1.7}\n.aixia-post .lead{font-size:19px;line-height:1.65;color:#334155}\n.aixia-post h2{font-size:21px!important;line-height:1.3!important;margin:36px 0 12px!important;font-weight:650!important;letter-spacing:-.2px;color:#0f172a}\n.aixia-post h2:before{content:\"\";display:block;width:34px;height:3px;border-radius:2px;background:#0b5fff;margin-bottom:12px}\n.aixia-post p{margin:0 0 16px}\n.aixia-post .cta{background:#f0f6ff;border:1px solid #dbe7ff;border-left:4px solid #0b5fff;border-radius:10px;padding:16px 20px;margin:28px 0}\n.aixia-post .cta p{margin:0}\n.aixia-post ul,.aixia-post ol{padding-left:22px;margin:0 0 16px}\n.aixia-post li{margin:0 0 8px}\n.aixia-post table{width:100%;border-collapse:collapse;margin:20px 0;font-size:15px}\n.aixia-post th,.aixia-post td{border:1px solid #e5e7eb;padding:10px 12px;text-align:left;vertical-align:top}\n.aixia-post th{background:#f8fafc;font-weight:600}\n<\/style>\n<div class=\"aixia-post\">\n<p class=\"lead\">Efterfr\u00e5gan p\u00e5 GPU-kapacitet v\u00e4xer snabbare \u00e4n de flesta organisationer hinner planera f\u00f6r. Det som f\u00f6r n\u00e5gra \u00e5r sedan var ett forskningsprojekt \u00e4r i dag en produktionsplattform, med krav p\u00e5 tillg\u00e4nglighet, s\u00e4kerhet och f\u00f6ruts\u00e4gbara kostnader. Samtidigt drar norra Europa till sig stora datacenterinvesteringar tack vare tillg\u00e5ng till f\u00f6rnybar el och ett klimat som g\u00f6r kylningen enklare.<\/p>\n<p>F\u00f6r den som ska bygga eller ut\u00f6ka sin AI-infrastruktur v\u00e4cker det en fr\u00e5ga som inte l\u00e4ngre bara \u00e4r teknisk: var ska ber\u00e4kningskraften ligga? I publika moln, i egna datacenter, hos en colocation-leverant\u00f6r eller i en kombination? Svaret p\u00e5verkar kostnader, prestanda, regelefterlevnad och hur fritt ni kan r\u00f6ra er fram\u00e5t. H\u00e4r resonerar vi kring hur man fattar det beslutet, och vad organisationer inom f\u00f6rsvar, medtech och automotive beh\u00f6ver ta s\u00e4rskild h\u00e4nsyn till.<\/p>\n<h2>Varf\u00f6r Norden lockar<\/h2>\n<p>Moderna GPU-system f\u00f6rbrukar betydligt mer energi per rack \u00e4n traditionell IT, och en v\u00e4xande andel kr\u00e4ver v\u00e4tskekylning. Det g\u00f6r tillg\u00e5ngen till el och effektiv kylning till avg\u00f6rande faktorer n\u00e4r man v\u00e4ljer placering. H\u00e4r har Norden flera f\u00f6rdelar: en stor andel f\u00f6rnybar el, ett kallt klimat som m\u00f6jligg\u00f6r frikyla stora delar av \u00e5ret och stabila politiska och regulatoriska f\u00f6rh\u00e5llanden. Det finns ocks\u00e5 en h\u00e5llbarhetsdimension &#8211; allt fler organisationer beh\u00f6ver redovisa klimatp\u00e5verkan fr\u00e5n sin IT, och AI-tr\u00e4ning p\u00e5 el med l\u00e5ga utsl\u00e4pp g\u00f6r stor skillnad i den redovisningen.<\/p>\n<p>Samtidigt \u00e4r bilden inte helt okomplicerad. Eln\u00e4tskapaciteten \u00e4r begr\u00e4nsad p\u00e5 flera h\u00e5ll, s\u00e4rskilt i s\u00f6dra Sverige, och det kan ta l\u00e5ng tid att f\u00e5 ny effekt ansluten. Elpriset skiljer sig ocks\u00e5 mellan elomr\u00e5dena. Den som planerar en st\u00f6rre GPU-installation beh\u00f6ver d\u00e4rf\u00f6r b\u00f6rja med fr\u00e5gan om effekt och kylning i ett tidigt skede, inte n\u00e4r h\u00e5rdvaran redan \u00e4r best\u00e4lld.<\/p>\n<h2>Moln, eget eller colocation?<\/h2>\n<p>Det finns inget alternativ som \u00e4r b\u00e4st i alla l\u00e4gen. Publika moln ger snabb tillg\u00e5ng och flexibilitet, egen infrastruktur ger kontroll och l\u00e4gre kostnad vid h\u00f6g bel\u00e4ggning, och colocation hamnar n\u00e5gonstans d\u00e4remellan. De flesta organisationer vi m\u00f6ter landar i en hybrid, d\u00e4r olika delar av AI-arbetet placeras d\u00e4r de g\u00f6r mest nytta &#8211; en stabil bas av egen eller colocerad kapacitet f\u00f6r det som k\u00f6rs kontinuerligt, och moln f\u00f6r toppar, experiment och tillf\u00e4lliga projekt.<\/p>\n<p>Den enskilt viktigaste faktorn f\u00f6r kostnaden \u00e4r utnyttjandegraden. En GPU i molnet kostar per timme oavsett hur mycket den anv\u00e4nds, medan egen h\u00e5rdvara \u00e4r en fast kostnad som blir billigare ju mer den anv\u00e4nds. Har ni ett j\u00e4mnt och h\u00f6gt behov \u00f6ver tid blir egen kapacitet ofta betydligt mer kostnadseffektiv; \u00e4r behovet oj\u00e4mnt eller os\u00e4kert kan molnet vara r\u00e4tt, \u00e5tminstone till en b\u00f6rjan.<\/p>\n<p>N\u00e4sta fr\u00e5ga \u00e4r var datan finns. Stora dataset \u00e4r dyra och tidskr\u00e4vande att flytta, och i molnet tillkommer ofta avgifter f\u00f6r att h\u00e4mta ut data igen. Det brukar kallas data gravity: ber\u00e4kningskraften dras mot datan, inte tv\u00e4rtom. Tr\u00e4ning och inferens har dessutom olika behov &#8211; tr\u00e4ning \u00e4r tolerant mot avst\u00e5nd men kr\u00e4ver mycket kapacitet under l\u00e5nga perioder, medan inferens ligger n\u00e4rmare anv\u00e4ndarna och verksamheten d\u00e4r svarstider och integration v\u00e4ger tyngre. Att skilja p\u00e5 de tv\u00e5 \u00e4r ofta det f\u00f6rsta steget mot en genomt\u00e4nkt placering.<\/p>\n<table>\n<thead>\n<tr>\n<th><\/th>\n<th>Publikt moln<\/th>\n<th>Colocation<\/th>\n<th>Eget datacenter<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Tid till kapacitet<\/td>\n<td>Snabbt, om GPU:er finns tillg\u00e4ngliga<\/td>\n<td>Medel, beroende p\u00e5 leveranstid f\u00f6r h\u00e5rdvara<\/td>\n<td>L\u00e4ngst, kr\u00e4ver effekt, kylning och lokaler<\/td>\n<\/tr>\n<tr>\n<td>Kostnad vid h\u00f6g bel\u00e4ggning<\/td>\n<td>H\u00f6g<\/td>\n<td>L\u00e4gre<\/td>\n<td>L\u00e4gst p\u00e5 sikt, h\u00f6gst initial investering<\/td>\n<\/tr>\n<tr>\n<td>Flexibilitet<\/td>\n<td>H\u00f6g, skala upp och ner efter behov<\/td>\n<td>Medel<\/td>\n<td>L\u00e5g, kapaciteten \u00e4r fast<\/td>\n<\/tr>\n<tr>\n<td>Kontroll \u00f6ver data<\/td>\n<td>Begr\u00e4nsad, beror p\u00e5 leverant\u00f6r och jurisdiktion<\/td>\n<td>H\u00f6g<\/td>\n<td>Full<\/td>\n<\/tr>\n<tr>\n<td>Krav p\u00e5 egen kompetens<\/td>\n<td>L\u00e5g f\u00f6r drift, h\u00f6g f\u00f6r kostnadsstyrning<\/td>\n<td>Medel<\/td>\n<td>H\u00f6g<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2>Branschkrav som styr placeringen<\/h2>\n<p>Grundfr\u00e5gorna \u00e4r desamma i alla branscher, men vissa verksamheter har krav som i praktiken avg\u00f6r placeringen innan kostnadskalkylen ens \u00e4r gjord.<\/p>\n<p><strong>F\u00f6rsvar och s\u00e4kerhetsk\u00e4nslig verksamhet.<\/strong> F\u00f6r f\u00f6rsvarsindustrin och myndigheter \u00e4r kontroll \u00f6ver data och infrastruktur ofta ett absolut krav. S\u00e4kerhetsskyddslagstiftningen, sekretess och exportkontroll g\u00f6r att publika moln s\u00e4llan \u00e4r ett alternativ f\u00f6r k\u00e4nsliga workloads. Det handlar inte bara om var datan lagras, utan ocks\u00e5 om vem som har \u00e5tkomst till systemen och under vilken jurisdiktion leverant\u00f6ren verkar &#8211; amerikansk lagstiftning som CLOUD Act \u00e4r en faktor som m\u00e5nga beh\u00f6ver f\u00f6rh\u00e5lla sig till. H\u00e4r blir egen infrastruktur, ibland helt avskild fr\u00e5n internet, ofta den enda v\u00e4gen, vilket i sin tur kr\u00e4ver att plattformen g\u00e5r att drifta och uppdatera i en sluten milj\u00f6.<\/p>\n<p><strong>Medtech och life science.<\/strong> Inom medtech handlar det om patientdata, GDPR och regelverk som MDR f\u00f6r medicintekniska produkter. Kraven p\u00e5 sp\u00e5rbarhet och validering g\u00f6r att det m\u00e5ste g\u00e5 att visa exakt vilken data och vilken modellversion som anv\u00e4nts, och att milj\u00f6n \u00e4r kontrollerad. M\u00e5nga v\u00e4ljer att tr\u00e4na p\u00e5 egen eller colocerad infrastruktur inom EU och anv\u00e4nda molnet f\u00f6r mindre k\u00e4nsliga delar, som utveckling med syntetisk eller anonymiserad data. En tydlig strategi f\u00f6r var data f\u00e5r finnas \u00e4r minst lika viktig som valet av h\u00e5rdvara.<\/p>\n<p><strong>Automotive.<\/strong> Automotive-branschen hanterar enorma datam\u00e4ngder fr\u00e5n testfordon, sensorer och simuleringar, ofta i storleksordningen petabyte. H\u00e4r \u00e4r data gravity den dominerande faktorn: det \u00e4r helt enkelt inte rimligt att skicka all data fram och tillbaka till ett moln. Samtidigt \u00e4r behovet av compute stort och kontinuerligt, vilket talar f\u00f6r egen kapacitet med h\u00f6g utnyttjandegrad. Krav p\u00e5 informationss\u00e4kerhet fr\u00e5n fordonstillverkare, till exempel enligt TISAX, p\u00e5verkar ocks\u00e5 hur milj\u00f6n ska byggas och dokumenteras.<\/p>\n<h2>Fr\u00e5n strategi till fungerande plattform<\/h2>\n<p>En bra compute-strategi b\u00f6rjar s\u00e4llan med h\u00e5rdvaran. Den b\u00f6rjar med verksamhetens behov och de krav som inte g\u00e5r att f\u00f6rhandla bort. Vi brukar arbeta utifr\u00e5n n\u00e5gra fr\u00e5gor:<\/p>\n<ol>\n<li><strong>Vilka krav \u00e4r absoluta?<\/strong> S\u00e4kerhetsskydd, regelefterlevnad och krav p\u00e5 datans placering s\u00e4tter ramarna f\u00f6r allt annat.<\/li>\n<li><strong>Hur ser behovet ut \u00f6ver tid?<\/strong> Ett j\u00e4mnt, h\u00f6gt behov talar f\u00f6r egen kapacitet. Oj\u00e4mna toppar talar f\u00f6r att komplettera med moln.<\/li>\n<li><strong>Var finns datan, och var skapas den?<\/strong> Placera compute n\u00e4ra den data som \u00e4r tyngst att flytta.<\/li>\n<li><strong>Vad ska k\u00f6ras var?<\/strong> Skilj p\u00e5 tr\u00e4ning, finjustering och inferens &#8211; de har olika krav och kan med f\u00f6rdel ligga p\u00e5 olika st\u00e4llen.<\/li>\n<li><strong>Vem ska drifta plattformen?<\/strong> Egen infrastruktur kr\u00e4ver kompetens inom drift, MLOps och s\u00e4kerhet. Saknas den internt beh\u00f6ver den l\u00f6sas genom en partner.<\/li>\n<li><strong>Hur ser v\u00e4gen fram\u00e5t ut?<\/strong> Planera f\u00f6r effekt, kylning och n\u00e4tverk s\u00e5 att plattformen kan v\u00e4xa utan att byggas om.<\/li>\n<\/ol>\n<p>Aixia \u00e4r Skandinaviens enda NVIDIA DGX SuperPOD-certifierade partner och har l\u00e5ng erfarenhet av att bygga AI-infrastruktur f\u00f6r organisationer med h\u00f6ga krav p\u00e5 s\u00e4kerhet och prestanda. Vi hj\u00e4lper till hela v\u00e4gen, fr\u00e5n placering, effekt och kylning till compute, n\u00e4tverk, lagring och drift, och med v\u00e5r MLOps-plattform AiQu blir infrastrukturen n\u00e5got era team faktiskt kan arbeta i. Oavsett om svaret blir eget datacenter, colocation, moln eller en kombination b\u00f6rjar vi med era behov och krav, inte med en f\u00e4rdig l\u00f6sning.<\/p>\n<div class=\"cta\">\n<p><strong>Boka en genomg\u00e5ng av er compute-strategi.<\/strong> Tillsammans tittar vi p\u00e5 era workloads, era krav och er tillv\u00e4xtplan, och tar fram en rekommendation f\u00f6r var er AI-infrastruktur b\u00f6r ligga.<\/p>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Where should computing power be located? A public cloud, an on-premises data center, colocation, or a combination? Here\u2019s how to make that decision\u2014and what the defense, medtech, and automotive industries should consider.<\/p>\n","protected":false},"author":15,"featured_media":122128,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"om_disable_all_campaigns":false,"inline_featured_image":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[60],"tags":[],"class_list":["post-122176","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-blog"],"acf":[],"aioseo_notices":[],"aioseo_head":"\n\t\t<!-- All in One SEO 5.0.0.1 - aioseo.com -->\n\t<meta name=\"description\" content=\"Where should computing power be located? A public cloud, an on-premises data center, colocation, or a combination? 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