Razer’s Upcoming Intel-Powered Switch 13 Will Offer 25W Switchable TDP


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When Intel took the lid off of Ice Lake, we noted that the performance data for the CPU was complex. On the GPU side of things, Ice Lake is a huge leap forward, with substantially higher performance than anything we’ve seen from Intel integrated graphics before. The CPU, however, was a rather mixed bag. When restrained to a 15W TDP, Ice Lake CPUs weren’t necessarily faster than the Coffee Lake chips they are intended to replace and were often somewhat slower. If you give the CPU additional headroom, this problem resolves — but of course, giving the chip more power to play with has a negative impact on heat and battery life.

When Intel invited reviewers to test Ice Lake, the test systems it offered had a toggle switch to flip from 15W to 25W envelopes. That’s how PCMag and other publications were able to test the laptop in both modes, as shown below:

Users don’t usually have this kind of option. TDP ranges are typically pre-defined by the OEM and are not something that the end user can modify, for obvious reasons — cranking up laptop TDP is a good way to overheat the system if you don’t know what you’re doing and if the laptop isn’t specifically designed to run at the higher power level. To the best of our knowledge (until today), no consumer laptop could actually change its TDP values on the fly. At the Ice Lake testing event, Intel told reviewers that the Ice Lake laptops sold at retail wouldn’t have this option, either.

There appears to be at least one exception to this rule, however. The Razer Blade 13 will have an adjustable TDP that can be configured through Razer’s Synapse software. Supposedly this capability has always existed, going back to the original Razer Blade. If this is true, it’s not something the company previously seems to have highlighted — Google doesn’t bring up any results referring to an adjustable TDP on previous versions of the Razer Blade,SEEAMAZON_ET_135 See Amazon ET commerce unless you count the fact that the laptop would down-clock under load in some circumstances. To be clear, the ability to run the CPU in a lower power envelope under load isn’t the same thing as being able to voluntarily put it in a higher TDP mode and operate it with additional power headroom.

Given that Intel had already told reviewers not to expect adjustable TDP ranges as a major laptop feature, this raises the question: Is this specific to Razer, or will we see more laptop manufacturers taking advantage of these new capabilities? Will Intel make adjustable TDPs a feature that high-end customers can shell out for if they want the option?

Razer’s website for the new Blade states that the system will use a 25W Ice Lake CPU, but does not mention anything about the system being adjustable within a 15W versus a 25W power envelope.

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Intel’s Cascade Lake With DL Boost Goes Head to Head with Nvidia’s Titan RTX in AI Tests


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For the past few years, Intel has talked up its Cascade Lake servers with DL Boost (also known as VNNI, Vector Neural Net Instructions). These new capabilities are a subset of AVX-512 and are intended to specifically accelerate CPU performance in AI applications. Historically, many AI applications have favored GPUs over CPUs. The architecture of GPUs — massively parallel processors with low single-thread performance — has been a much better fit for graphics processors rather than CPUs. CPUs offer far more execution resources per thread, but even today’s multi-core CPUs are dwarfed by the parallelism available in a high-end GPU core.

Anandtech has compared the performance of Cascade Lake, the Epyc 7601 (soon to be surpassed by AMD’s 7nm Rome CPUs, but still AMD’s leading server core today), and an RTX Titan. The article, by the excellent Johan De Gelas, discusses different types of neural nets beyond the CNNs (Convolutional Neural Networks) that are typically benchmarked, and how a key part of Intel’s strategy is to compete against Nvidia in workloads where GPUs are not as strong or cannot yet serve the emerging needs of the market due to constraints on memory capacity (GPUs still can’t match CPUs here), the use of ‘light’ AI models that don’t require long training times, or AI models that depend on non-neural network statistical models.

Growing data center revenue is a critical component of Intel’s overall push into AI and machine learning. Nvidia, meanwhile, is keen to protect a market that it currently competes in virtually alone. Intel’s AI strategy is broad and encompasses multiple products, from Movidius and Nervana to DL Boost on Xeon, to the upcoming Xe line of GPUs. Nvidia is seeking to show that GPUs can be used to handle AI calculations in a broader range of workloads. Intel is building new AI capabilities into existing products, fielding new hardware that it hopes will impact the market, and trying to build its first serious GPU to challenge the work AMD and Nvidia do across the consumer space.

What Anandtech’s benchmarks show, in aggregate, is that the gulf between Intel and Nvidia remains wide — even with DL Boost. This graph of a Recurrent Neural Network test used a “Long Short-Term Memory (LSTM) network as neural network. A type of RNN, LSTM selectively “remembers” patterns over a certain duration of time.” Anandtech also used three different configurations to test it — out-of-the-box Tensorflow with conda, an Intel-optimized Tensorflow with PyPi, and a version of Tensorflow optimized from-source using Bazel, using the very latest version of Tensorflow.

Image by Anandtech

 

Image by Anandtech

 

This pair of images captures relative scaling between the CPUs as well as the comparison against the RTX Titan. Out of the box performance was quite poor on AMD, though it improved with the optimized code. Intel’s performance shot up like a rocket when the source-optimized version was tested, but even the source-optimized version didn’t match Titan RTX performance very well. De Gelas notes: “Secondly, we were quite amazed that our Titan RTX was less than 3 times faster than our dual Xeon setup,” which tells you something about how these comparisons run within the larger article.

DL Boost isn’t enough to close the gap between Intel and Nvidia, but in fairness, it probably was never supposed to be. Intel’s goal here is to improve AI performance enough on Xeon to make running these workloads plausible on servers that will be mostly used for other things, or when building AI models that don’t fit within the constraints of a modern GPU. The company’s longer-term goal is to compete in the AI market with a range of equipment, not just Xeons. With Xe not quite ready yet, competing in the HPC space right now means competing with Xeon.

For those of you wondering about AMD, AMD isn’t really talking about running AI workloads on Epyc CPUs, but has focused on its RocM initiative for running CUDA code on OpenCL. AMD does not talk about this side of its business very much, but Nvidia dominates the market for AI and HPC GPU applications. Both AMD and Intel want a piece of the space. Right now, both appear to be fighting uphill to claim one.

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Intel Reveals Clock Speeds, GPU Specs for 10nm Ice Lake Mobile SoCs


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Last week, Intel announced that it had begun shipping 10nm Ice Lake CPUs to its OEM customers to support a holidays 2019 launch. Today, the company is sharing more details about Ice Lake and the new chips it will launch on 10nm later this year. The company has been revealing details about Ice Lake and its architecture, Sunny Cove, since Architecture Day last winter. As “Holidays 2019” draws closer, we’re starting to find out more information.

With 10nm, Intel is pushing forward on multiple fronts. CPU-wise, the company expects to offer up to 1.18x improved IPC, though that gain is largely offset by declines in top-end frequency. Intel’s own slides show a relatively small gain in terms of raw performance over and above Whiskey Lake,SEEAMAZON_ET_135 See Amazon ET commerce though users with older systems based on Broadwell or Skylake will see much larger improvements.

Intel-Slide-10nm-2

Ice Lake packs a grab bag of improvements intended to appeal to multiple different markets. Boosted AI inferencing performance is potentially appealing to those working in the field, though I’m not sure if any practical applications actually use AI or AVX-512 on the desktop yet. Faster Wi-Fi via 802.11ax, aka Wi-Fi 6, should boost download speeds. Thunderbolt 3 is not integrated on-die with Intel Ice Lake, though actually offering that connectivity to customers will still require a degree of external hardware and is therefore somewhat dependent on OEMs to make available. Intel has stated, however, that the costs and amount of external components will be smaller than usual.

Mobile GPU performance is said to be significantly stronger, courtesy of a wider GPU core and more efficient execution. Ice Lake will support either dual-channel DDR4-3200 or LPDDR4X-3733 in four 32-bit channels. Overall power consumption is said to be similar between both standards, though the LPDDR4X systems will top out at 32GB, while the DDR4-3200 rigs will support up to 64GB. Our slideshow on the Sunny Cove architecture and the various improvements baked into the core is presented below:

One new bit of data Intel is revealing today is the actual SKUs and products. Here’s the lineup of 10th Generation mobile parts, with data on their wattage envelopes, clocks, and GPU configurations.

Intel-Slide-10nm-1

Let’s start with the 28W CPU. The best comparison to that is the Core i7-8569U, a 28W 4C/8T CPU with a 2.8GHz base clock, 4.7GHz boost clock, and 128MB of onboard EDRAM to improve the performance of its integrated Iris Plus Graphics 655 solution. We will immediately grant that we expect Gen 11 Intel graphics to be faster than the EDRAM-boosted solutions the company has used before. We also note that the 10nm Ice Lake Core i7-1068G7 supports faster RAM (DDR4-3200 / LPDDR4-3733 as compared to DDR4-2400). Intel CPUs typically haven’t benefited as much from faster RAM clocks as AMD CPUs, but the fact that Intel is increasing its RAM clock suport with 10nm may mean this has changed.

Both CPU and GPU maximum frequencies have declined. The Core i7-8569U has a maximum GPU frequency of 1.2GHz, while the Core i7-1068G7 supports a maximum frequency of 1.1GHz. Base frequency for the 10th Generation core CPU has dropped 18 percent. Since we know that Intel TDPs are based solely on boost clocks, the implication is that the company had to give up base clock to make its TDP figures.

The 15W minimum frequencies have also come down. The Core i7-1065G7 has a base frequency of 1.3GHz, while the comparative Core i7-8665U is a 1.9GHz CPU with a 4.8GHz base clock. That’s a 32 percent reduction in minimum frequency. I don’t want to sound negative on Ice Lake before we see the chips. It’s possible that some of the clock pulldown has been to make room for the GPU. But this is a point we’ll be watching closely — Intel may have had to strike a difficult balance between allocating TDP for CPU versus GPU operations.

Word from Intel is that Ice Lake will be built on a 10nm+ process, which puts that question to rest. The little-used Cannon Lake Core i3-8121 will evidently be the sole representative of Intel’s base 10nm process. 10nm+ will debut with Ice Lake. Whether Intel has a 10nm++ process in the works or will proceed directly to 7nm for future CPUs isn’t something the company has disclosed yet.

For more on this and some initial benchmarks, read PCMag’s Intel ‘Ice Lake’ Benchmarked: How 10nm CPUs Could Bring Major GPU Grunt to New Laptops.

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