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MCDRAM

MCDRAM is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand MCDRAM rather than just read about it. In short: Multi-Channel DRAM or MCDRAM (pronounced em cee dee ram) is a 3D-stacked DRAM that is used in the Intel Xeon Phi processor codenamed Knights Landing. It is a version of Hybrid Memory Cube developed in partnership with Micron Technology, and a competitor to High Bandwidth Memory.

Key takeaways

  • MCDRAM belongs to computer science; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect MCDRAM to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of MCDRAM from memory before moving on to harder problems.

Reference excerpt

Multi-Channel DRAM or MCDRAM (pronounced em cee dee ram) is a 3D-stacked DRAM that is used in the Intel Xeon Phi processor codenamed Knights Landing. It is a version of Hybrid Memory Cube developed in partnership with Micron Technology, and a competitor to High Bandwidth Memory. The many cores in the Xeon Phi processors, along with their associated vector processing units, enable them to consume many more gigabytes per second than traditional DRAM DIMMs can supply. The "Multi-channel" part of the MCDRAM full name reflects the cores having many more channels available to access the MCDRAM than processors have to access their attached DIMMs. This high channel count leads to MCDRAM's high bandwidth, up to 400+ GB/s, although the latencies are similar to a DIMM access. Its physical placement on the processor imposes some limits on capacity – up to 16 GB at launch, although speculated to go higher in the future.

Programming The memory can be partitioned at boot time, with some used as cache for more distant DDR, and the remainder mapped into the physical address space. The application can request pages of virtual memory to be assigned to either the distant DDR directly, to the portion of DDR that is cached by the MCDRAM, or to the portion of the MCDRAM that is not being used as cache. One way to do this is via thememkind API. When used as cache, the latency of a miss accessing both the MCDRAM and DDR is slightly higher than going directly to DDR, and so applications may need to be tuned to avoid excessive cache misses.

References

External links

MCDRAM (High Bandwidth Memory) on Knights Landing – Analysis Methods & Tools An Intro to MCDRAM (High Bandwidth Memory) on Knights Landing High Bandwidth Memory (HBM): how will it benefit your application? Micron HMC Webinar July 2017 slides

Worked examples

Example 1 — a first encounter with MCDRAM

Start with the simplest possible case. Write down what MCDRAM claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to MCDRAM before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about MCDRAM ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of MCDRAM

In research
MCDRAM appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses MCDRAM in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
MCDRAM is common in secondary-school and first-year university syllabi. It links to neighbouring topics Computer-related introductions in 2016, Computer architecture, Computer memory, so understanding it makes those chapters shorter.
In everyday life
Look for MCDRAM outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study MCDRAM in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what MCDRAM means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain MCDRAM out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is MCDRAM in simple terms?

Multi-Channel DRAM or MCDRAM (pronounced em cee dee ram) is a 3D-stacked DRAM that is used in the Intel Xeon Phi processor codenamed Knights Landing. It is a version of Hybrid Memory Cube developed in partnership with Micron Technology, and a competitor to High Bandwidth Memory.

Why does MCDRAM matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study MCDRAM?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on MCDRAM.

Tags

  • Computer-related introductions in 2016
  • Computer architecture
  • Computer memory
  • Intel
  • Parallel computing

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