CAD Tech News (#148)17 Jun, 2021 By: Cadalyst Staff
Herrera on Hardware:
AMD's RDNA2 Architecture Arrives for CAD Professionals
Cadalyst looks at the two new Radeon Pro models first out of the chute.
By Alex Herrera
NVIDIA has been hogging the spotlight in the world of professional visual computing lately, aggressively rolling out RTX-brand A-series products on the back of its latest Ampere generation technology (covered initially here and fleshed out further here). But while the company dominates the market for professional GPUs, it’s not the only game in town. This month, AMD served notice it remains committed to the demands of applications such as CAD, releasing the first members of a new generation of Radeon Pro products that leverage the advancements of the company’s latest GPU microarchitecture.
The Second-Generation RDNA GPU
When it comes to building a next-generation GPU, there are two basic tools at a chip architect’s disposal: the microarchitecture which typically is upgraded from generation to generation to improve efficiency, along with the periodic ground-up rebuild, and the transistors available, measured in both density and performance. The transistors improve as a function of manufacturing density, albeit allocated at the discretion of the vendor, since bigger chips cost more in both dollars and watt use.
On firm ground with respect to silicon manufacturing, AMD has at its disposal TSMC’s (Taiwan Semiconductor Manufacturing Corp.) 7 nm process, which for all intents and purposes today represents the best transistor density available. The first RDNA 2 chip, the max-capacity flagship “Big Navi” (a.k.a., Navi 21) integrates an impressive 26.8-billion transistors. Bear in mind that typically the biggest, most powerful chip is released first, with trimmed-down lower-cost derivatives following after. That’s precisely what we’re seeing so far in the in RDNA 2 generation, with the release of the both workstation-caliber Radeon Pro GPUs as well as the economical Radeon cards designed for gaming.
The first RDNA 2 chip, Big Navi, is built on RDNA 2 with 26.8-billion transistors in 7 nm. (Image source: AMD)
RDNA 2 Upgrades
Let’s look at the new generation’s microarchitecture. As its name might suggest, RDNA 2 is not one of the ground-up rebuilds we occasionally see, but a more modest yet compelling enhancement of the preceding RDNA microarchitecture. There’s one very noteworthy and significant architectural upgrade to RDNA’s core processing Compute Unit (CU) that I’ll cover later in this article. Otherwise, the more important advancement is not so much about the CU’s structure as it is its count, with the max incarnation of Big Navi implementing 80 CUs (and different SKUs exposing 80 or fewer). Second generation optimizations on the mature 7 nm process also brought clock rates up as well in excess of 2GHz internally, and the combination delivers on the overall CU throughput improvement.
From an implementation standpoint, the most significant departure (and step forward) I see in RDNA2 is its Infinity Cache. Based on the L3 cache gleaned from the company’s Zen 3 CPU core, the Infinity Cache delivers 128MB of on-chip memory. That ample size operating at fast internal rates allowed AMD engineers to drop the external memory interface from the typical 384 bit width down to 256 bits. The combination of Infinity Cache and the narrower interface allows Big Navi to deliver 2X the bandwidth of a conventional 384-bit GDDR6 interface.
Why not just leverage the benefits of more cache and keep the wider interface to get that much more bandwidth? In one word, power. Big Navi, along with all high performance GPUs today, bumps up against practical power limits, both in terms of supplying the power and dissipating the resulting heat. 250 to 300 watts tend to be the range vendors don’t want to exceed. Even with the narrow interface, Big Navi uses 250 watts. Clearly, the Infinity Cache was a favored solution both for performance and power reduction, and retaining the wider external interface would simply push power consumption too far.
RDNA 2’s Infinity Cache allows AMD to double the bandwidth of a conventional 384b GDDR6 interface, while cutting a bit of power. (Image source: AMD)
All told, AMD promises RDNA2 will roughly deliver 79% higher relative performance (across SKUs), and by combining the increase in performance while cutting and/or maintaining power limits, the company also claims a 54% improvement in Big Navi’s performance/watt, as compared to first generation RDNA.
What About Ray Tracing?
3D graphics remains the foundation of professional visual computing, as much as in CAD spaces as anywhere else. And while it will likely remain the mainstay of CAD visuals for some time, AMD’s rival NVIDIA is betting that physically based rendering will represent the long term future for 3D, both with respect to modeling and gaming. It’s made that position clear and aggressive, as evidenced by its introduction of ray tracing acceleration with 2018–19’s Turing — and affirmed with 2020’s Ampere. I am a believer in the long-term push toward enabling pervasive rendering, and as more CAD users experience the superior visuals — more frequently and with finer level of detail — I imagine there will be more than a few converts among the AEC, manufacturing, and design communities. (For a more detailed dive into the fundamental differences in 3D rendering versus 3D graphics, check out my previous column covering the launch of RTX in NVIDIA’a Volta generation GPU, as well as this follow-on introducing RT cores in Turing, the successor to Volta and predecessor to Ampere.)
There really is no substitute for physically based rendering when conveying the ultimate look and feel of a design. (Image source: AMD, produced with ProRender)
With NVIDIA driving the GPU market, particularly among professional-focused GPUs serving CAD applications, AMD needed to provide some ray tracing oomph in its next generation hardware. And, it has.
Let’s circle back to my earlier reference to RDNA 2’s improvement to its core Compute Unit (CU). The most notable upgrade is the addition of one Ray Accelerator (RA) per CU. Similar to the purpose behind NVIDIA’s RT Core, the RA handles the more cumbersome and compute-intensive calculation for intersecting rays and surfaces, a critical performance path in the overall rendering workload. The ability to fire more rays and trace their path through the 3D scene should mean significantly higher throughput. I have not (yet) had the chance to quantitatively compare rendering throughput in a meaningful way, but AMD’s inclusion of dedicated hardware should make RDNA 2 generation GPU ray tracing performance competitive.
Continue reading to understand how GPU memory can play an important role in rendering; read up on the specs for these new products, and more of what the new technology is capable of!
Alex Herrera is a consultant focusing on high-performance graphics and workstations.
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Innovation FabLab’s new wind turbine, collaboratively designed within Wikifactory’s Workspace.
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