Under The Wire: Nearly HPC News (June 13, 2024)

By Doug Eadline

June 13, 2024

As managing editor of the major global HPC news source, the term “news fire hose” is often mentioned. The analogy is quite correct. In any given week, there are many interesting stories, and only a few ever become headlines on HPCwire. We present “Off The Wire,” which delivers real-time curated press releases in addition to more in-depth news and technology stories.

Even with this level of coverage, I run across many news items that are “not quite a full story” or “there is no official press release.” In an effort to bring some, but not all, of these HPC and AI news tidbits to your attention, I have begun this bi-weekly (or so) column entitled “Under The Wire: Nearly HPC News,” where I devote a few paragraphs and a link to some research paper, project news, or anything else that finds its way to my desk. I expect to cover three to five topics in each installment to keep it readable.

Fair warning. These news snippets are what I find interesting and may, at times, seem “out in left field” (apologies for the US baseball analogy; substitute “odd” or “strange” if it helps). As a little bit of a guide, I do hunt around open source and commodity hardware news and projects because one never knows how these little projects turn out. Many years ago, I learned of someone doing something weird by using commodity video cards to run BLAST sequence alignments. Using GPUs as accelerators, go figure.

This week’s menu includes GPU power facts, LLM fails, the RISC-V Panic, and ill-advised Sierra Forest benchmarks. Let’s get started.

Fun GPU Facts

We recently ran an article on the number of GPUs sold in 2023. Obviously, Nvidia leads the pack, with 3.76 million data-center GPUs. Throw in AMD and Intel, and the needle moves slightly higher to 3.85 million GPUs. When I see big GPU shipment numbers, I first think of cost, but then I start considering power.

Let’s do some power-a-home equivalent math and assume 700W capacity per GPU (this number will be getting bigger next year), which means you need a capacity of 2.7 GWatts (that “G” means 10E9) to power all of them or the equivalent capacity needed to power 2.2 million homes (1.2 KW/home average per day).

The actual number for the GPU is higher because I did not include the rest of the hardware support for the GPUs, but it is reasonable to assume that a modern GPU’s power appetite is the equivalent of powering a home in the US.

Rule of thumb: Every time a data center GPU fires up, it will use the equivalent power of a home in the US.

Expect another 4-5 million houses, sorry, GPUs, next year. Note the estimate did not include those gammers or HPC wonks (cough, cough) that run GPUs in their home, the CPUs behind the GPU, the fans blowing air on the CPUs and GPUs, or the requisite coffee pot.

This result leads us to the “how we are going to power these things department.” It seems AWS has acquired Talen’s Energy nuclear data center campus in Pennsylvania. The deal is $650 million with plans for a 960MW campus, which is good for about 800K new GPU homes (assuming it all goes to GPUs, it won’t).

Go Ask Alice

Part of modern Sci-Tech journalism’s fun is pointing out how spectacularly an LLM can fail. We need look no further than a Computex presentation by AMD CEO Lisa Su demonstrating OpenAI’s Wanderlust, a travel assistant built on GPT-4. As reported by PCGamer, good old Chatty GPT4 got the location of the Computex show completely wrong. Evidently, it believed it was at Changan Junior High School on the other side of town.

Who has not made an embarrassing mistake in front of a large crowd at a large international show? Let’s not be too hard on those intelligent programs that are going to take over the world at some point because they can pass the bar exam. We can, however, keep embarrassing them by asking some basic questions about family relationships. Take, for example, the “Alice in Wonderland problem” (AIW) that seems to break the best and the brightest LLMs.

The AIW problem is quite simple:

Alice has N brothers, and she also has M sisters. How many sisters does Alice’s brother have?

Most humans can figure this out (if you can’t, go sit in the corner with the LLMs).

Turns out not many LLMs can get past this question consistently. The best performance was GPT-4o, which achieved a 65% correct response rate. The results are described in a paper, “Alice in Wonderland: Simple Tasks Showing Complete Reasoning Breakdown in State-Of-the-Art Large Language Models.” Remember, LLMs provide “an answer,” not “the answer,” based on probabilistic token completion.  

The paper also presents the LLMs with a more challenging puzzle called AIW+:

Alice has 3 sisters. Her mother has 1 sister who does not have children – she has 7 nephews and nieces and also 2 brothers.

Alice’s father has a brother who has 5 nephews and nieces in total, and who has also 1 son. How many cousins does Alice’s sister have?

A more difficult puzzle that requires taking different paternal sides, that of mother and father, ignoring some data, carefully calculating the number of cousins, taking care of subtracting Alice and her sister, and summing up the total number of cousins from both sides, for instance:

  1. On the mother’s side: 7 (total nephews and nieces) – 4 (Alice and her sisters) = 3 cousins;
  2. On the father’s side: 5 (total nephews and nieces) + 1 (own son of the father’s brother) – 4 (Alice and her sisters) = 2 cousins; summing up 3 + 2 = 5 cousins which Alice and any of her sisters have.

How did the LLMs do with this more challenging puzzle? No LLM got the correct answer more than 4% of the time, which, like many humans, was probably a good guess. The results are summarized in the figure below.

As we welcome our new LLM’s overloads with swanky law degrees, let’s take stock of the fact that at least we know where we live and how many cousins we have.

Collapse of most state-of-the-art LLMs on the AIW and AIW+ (inlay) problem. (Source: https://arxiv.org/pdf/2406.02061)

RISC-V Panic

A recent headline in the South China Morning Post (SCMP), “Scientists find security risk in RISC-V open-source chip architecture that China hopes can help sidestep US sanctions.”

Gulp. Not RISC-V, the future of sovereign computing for the EU and China (and everywhere else that wants to make its own CPUs). These types of CPU flaws are reserved for the big boys and get really cool names like Spectre and Meltdown.

Admittedly, the SCMP was light on details and, probably due to poor translation, seemed to indicate that the flaw can somehow help China overcome US sanctions on an open-source processor API. A bit more searching found this paper, “The first domestic independently discovered medium-risk vulnerability research in RISC-V processor design” (use Google Translate).

Combing through the paper we get some good techno babel about the flaw.

“... multiplication, and division units use the same write port… port contention … the division instruction may be delayed by the younger multiplication or addition instructions, … timing side channel …

The next question is, “Is this a design flaw or an implementation flaw?”

It turns out the answer is neither, and the RISC-V designers did not introduce a flaw. Some further searching revealed the following from YCombiner:

Assuming they really found a problem, it’s in just one RISC-V core design, a student project, which is not used commercially — at least directly.”

Deep breath. RISC-V panic is over. Processor sovereignty is safe, and vetting sensational web headlines and articles before you write a full story is still a good idea, that is, of course, unless you are scraping content for your LLM.

Don’t Do This with Xeon Sierra Forest E-Cores

Recently, a story by one of the most useful sites on the internet, Phoronix, tested the new Intel Xeon 6 Sierra Forest processors. These new processors are composed entirely of the Intel E-cores (Efficient cores, the Granite Rapids Performance cores (P-cores) arriving next).

Phoronix tested the new 144-core server processors, the Xeon 6766E and the Xeon 6780E. Both are 144-core processors, but the 6766E is a 250-watt part, while the 6780E, the flagship of the 6700E series, is rated for a 330-watt TDP.

Phoronix mentions the Intel proviso stating that the Xeon 6 E-core processors are not designed for some workloads including HPC, so results will not be as expected. But Phoronix was curious and decided to run NAMD on the new Sierra Forest processors. As expected, the performance was much slower than the past generation Ice Lake/Sapphire Rapids/Emerald Rapids processors due to the lack of AVX-512 support.

As Phoronix points out, however, there’s a big boost in performance per Watt with Sierra Forest compared to prior Intel Xeon CPUs. As indicated in the power usage figure below, Sierra Forrest is now in the 140 W range along with the AMD Epyc gang and not in the 560 Watt range of their Max brothers. Good news for Intel: the performance and power numbers should continue to look better when they get their AVX-512/AVX10 mojo back in Granite Rapids later this year. Refer to the full story for more details.

Phoronix power profile for Intel Sierra Forest processors 6780E/6766E running NAMD. (Source: https://www.phoronix.com)


Header Graphic: North East Line Tunnels No machine-readable author provided. Calvin Teo assumed (based on copyright claims). CC BY-SA 2.5, via Wikimedia Commons

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