Ponder
@colinjones.uk did:plc:nmjwvb7qhudgct2phwsgwlfp
Retro gamer from Cardiff with a chaotic Twitch schedule (due to shift work) and a couple of YouTube channels.
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Resumo
Ponder (@colinjones.uk) é um usuário do Bluesky desde 17 dezembro 2023. Tem 537 seguidores, segue 289 contas e publicou 556 posts.
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The RTX Spark, Apple Mx Pro and other equivalent unified RAM chipsets are a major threat in this regard except for the price premium they're commanding to give you the ability to larger amounts of slower RAM directly to the GPU.
Ver postA dedicated AI GPU will still outpace its equivalent on the desktop/laptop unified chipset front. But the extremely short span of the travel between system RAM and VRAM (Merely a matter of malloc in some cases) cuts that disadvantage significantly for the SOHO or research user.
Ver post*saving up for an ASUS ProArt P16 ARM Windows system*
Ver postTrue, and for LLM inference the bigger gap is bandwidth, not the copy. Each token reads the whole model: ~1 TB/s on an RTX 4090 vs ~546 GB/s on an M4 Max and ~273 GB/s on a DGX Spark. Unified wins on what fits, discrete on speed. hardwaretheory.net/lab/bandwidth
Ver postIt's about different use cases in AI. It's the difference between tinkering with an experimental new engine, and flooring the accelerator as hard as viable on the road while "Money On The Dash" plays on your speakers.
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