{"id":22914,"date":"2025-11-30T13:46:41","date_gmt":"2025-11-30T18:46:41","guid":{"rendered":"https:\/\/carleton.ca\/scs\/?p=22914"},"modified":"2026-03-02T12:40:31","modified_gmt":"2026-03-02T17:40:31","slug":"unified-memory","status":"publish","type":"post","link":"https:\/\/carleton.ca\/scs\/2025\/unified-memory\/","title":{"rendered":"Unified Memory"},"content":{"rendered":"<p><span style=\"font-weight: 400;\">The term \u2018unified memory\u2019 has become more and more popular as of late and for good reason. More and more main computer components have been consolidated into a single microchip hence the term <\/span><b>SoC <\/b><span style=\"font-weight: 400;\">&#8211; \u2018System on a Chip\u2019. For years the <\/span><b>iGPU<\/b><span style=\"font-weight: 400;\"> &#8211; \u2018integrated Graphics Processor\u2019 exist so that you can display your computer&#8217;s output without the need of a dedicated graphics card. Now a new SoC design combining CPU, GPU and main memory on a single microchip are gaining popularity and are coined as unifying the memory or \u2018unified memory\u2019.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Computers with unified memory architecture feature a single shared pool of memory used by both the CPU and GPU, unlike traditional systems that have separate RAM and VRAM (see figure 1 &amp; 2). This unified design, popularised by Apple\u2019s M series chips, enables higher efficiency, reduced latency, and faster data transfer since the CPU and GPU work with the same memory space therefore don\u2019t need to travel using the overhead of the bus.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Consider the CPU generations categorised as follows:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">1st generation &#8211; 4-bit CPU<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">2nd generation &#8211; 8-bit CPU<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">3rd generation &#8211; 16-bit CPU<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">4th generation &#8211; 32-bit CPU<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">5th generation &#8211; 64-bit CPU<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">6th generation &#8211; multi-core CPU<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">7th generation &#8211; unified memory CPU<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">Unified memory is the next generation CPU and it will change the tech landscape. Now there will be an accessible alternative to high VRAM GPU\u2019s. This is what it means: you can use your computer main memory as graphics memory. Is this a big deal? Yes it is.Take the NVIDIA RTX PRO 6000 Blackwell GPU it has 96 GB of VRAM and at the time of this article costs $12k CAD. 128GB (2 x 64GB) 288-Pin PC RAM DDR5 6400 (PC5 51200) Desktop Memory costs $1,200 CAD. Do the Math, this GPU is 10x more expensive.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Unified memory RAM uses DDR4 or DDR5 shared between CPU and GPU. Its bandwidth can reach around 200-800 GB\/s. In contrast, dedicated GPU memory is optimized for very high bandwidth and low latency with wide interfaces 128-512 bits or more. Typical GPU VRAM bandwidth exceeds 500 GB\/s, sometimes over 1 TB\/s, and is directly connected to the GPU chip with minimal latency to feed thousands of CUDA cores efficiently. This difference alone can amount to a speed difference of a factor of 3-5. At this time GPU\u2019s are faster than a unified memory GPU.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Another new development in CPU design are the use of NPU\u2019s &#8211; Neural Processing Unit that accelerate neural networking operations part of the SoC design. These are marketed as AI CPU\u2019s and you will be seeing more and more of them. They will help speed up the tasks performed by digital assistants like Siri or Alexa and facial recognition for secure login and lots more.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Unified memory allows AI accelerators and processors to utilise the full RAM dynamically, which is beneficial for tasks like machine learning and LLM (Large Language Model) inference. The implications are you can use your computer&#8217;s main memory as VRAM and this is the biggest benefit of a unified memory PC. In a day and age where large VRAM GPU\u2019s are inaccessible, unified memory PC\u2019s give you an accessible option to run large parameter LLM\u2019s.<\/span><\/p>\n<p><a href=\"https:\/\/carleton.ca\/scs\/wp-content\/uploads\/unified-mem-cmp.png\"><img decoding=\"async\" loading=\"lazy\" class=\"size-full wp-image-22921 alignnone\" src=\"https:\/\/carleton.ca\/scs\/wp-content\/uploads\/unified-mem-cmp.png\" alt=\"\" width=\"808\" height=\"394\" srcset=\"https:\/\/carleton.ca\/scs\/wp-content\/uploads\/unified-mem-cmp.png 808w, https:\/\/carleton.ca\/scs\/wp-content\/uploads\/unified-mem-cmp-240x117.png 240w, https:\/\/carleton.ca\/scs\/wp-content\/uploads\/unified-mem-cmp-400x195.png 400w, https:\/\/carleton.ca\/scs\/wp-content\/uploads\/unified-mem-cmp-160x78.png 160w, https:\/\/carleton.ca\/scs\/wp-content\/uploads\/unified-mem-cmp-768x374.png 768w, https:\/\/carleton.ca\/scs\/wp-content\/uploads\/unified-mem-cmp-360x176.png 360w\" sizes=\"(max-width: 808px) 100vw, 808px\" \/><\/a><\/p>\n<p><span style=\"font-weight: 400;\">Here are some notable unified memory computers:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Apple M-chip computers lead this tech. A MAC mini can cost you less than $1k CAD.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">NVIDIA DGX Spark is the famous ARM + GPU \u201cAI Supercomputer on your desk\u201d and that will set you back more than $6,000 CAD.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">AMD best iGPU at this time is the Radeon 890M and benchmark\u2019s similar to an NVIDIA GTX 1070 GPU. Look for unified PC\u2019s with AMD Ryzen AI 9 tech inside.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Minisforum has combined the ARM CPU with their MS-R1 line of mini-PC\u2019s. You heard that right ARM for PC \u2013 not Intel or AMD but ARM.\u00a0 Advertised as \u201cthe first ARM mini-PC with a BIOS\u201d. Interestingly the first ARM based PC was the Acorn Archimedes 305 released 40 years ago.<\/span><\/li>\n<\/ul>\n<h3><span style=\"font-weight: 400;\">Terms used<\/span><\/h3>\n<ul>\n<li><b>Unified memory<\/b><span style=\"font-weight: 400;\"> &#8211; CPU and GPU share a single unified pool of memory<\/span><\/li>\n<li><b>SoC<\/b><span style=\"font-weight: 400;\"> &#8211; System on Chip. Consolidates the key components of a computer or electronic system onto a single microchip.<\/span><\/li>\n<li><b>iGPU<\/b><span style=\"font-weight: 400;\"> &#8211; integrated Graphics or graphics on the same die as a CPU<\/span><\/li>\n<li><b>VRAM <\/b><span style=\"font-weight: 400;\">&#8211; Video Random Access Memory is a type of dedicated memory used specifically by a graphics processing unit (GPU).<\/span><\/li>\n<li><b>NPU <\/b><span style=\"font-weight: 400;\">&#8211; Neural Processing Unit are specialized cores focused on accelerating neural network operations and commonly integrated into SoCs.<\/span><\/li>\n<\/ul>\n<p><\/p>\n<p><strong>Author<\/strong>:\u00a0<a href=\"https:\/\/carleton.ca\/scs\/people\/andrew-miles\/\">Andrew Miles<\/a>, Sr System Administrator, School of Computer Science, 杏吧原创 University<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The term \u2018unified memory\u2019 has become more and more popular as of late and for good reason. More and more main computer components have been consolidated into a single microchip hence the term SoC &#8211; \u2018System on a Chip\u2019. For years the iGPU &#8211; \u2018integrated Graphics Processor\u2019 exist so that you can display your computer&#8217;s [&hellip;]<\/p>\n","protected":false},"author":7,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_relevanssi_hide_post":"","_relevanssi_hide_content":"","_relevanssi_pin_for_all":"","_relevanssi_pin_keywords":"","_relevanssi_unpin_keywords":"","_relevanssi_related_keywords":"","_relevanssi_related_include_ids":"","_relevanssi_related_exclude_ids":"","_relevanssi_related_no_append":"","_relevanssi_related_not_related":"","_relevanssi_related_posts":"","_relevanssi_noindex_reason":"","_mi_skip_tracking":false,"_exactmetrics_sitenote_active":false,"_exactmetrics_sitenote_note":"","_exactmetrics_sitenote_category":0,"footnotes":"","_links_to":"","_links_to_target":""},"categories":[65],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.2 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Unified Memory - School of Computer Science<\/title>\n<meta name=\"description\" content=\"The term \u2018unified memory\u2019 has become more and more popular as of late and for good reason. 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