NVIDIA (NASDAQ: NVDA) today reported revenue for the third quarter ended October 30, 2022, of $5.93 billion, down 17% from a year ago and down 12% from the previous quarter. GAAP earnings per diluted share for the quarter were $0.27, down 72% from a year ago and up 4% from the previous quarter. Non-GAAP earnings per diluted share were $0.58, down 50% from a year ago and up 14% from the previous quarter.

"We are quickly adapting to the macro environment, correcting inventory levels and paving the way for new products," said Jensen Huang, founder and CEO of NVIDIA. "The ramp of our new platforms - Ada Lovelace RTX graphics, Hopper AI computing, BlueField and Quantum networking, Orin for autonomous vehicles and robotics, and Omniverse-is off to a great start and forms the foundation of our next phase of growth.

Supermicro, Inc., a Total IT Solution Provider for Cloud, AI/ML, Storage, and 5G/Edge, at the 2022 Super Computing Conference is unveiling the most extensive portfolio of servers and storage systems in the industry based on the upcoming 4th Gen Intel Xeon Scalable processor, formerly codenamed Sapphire Rapids. Supermicro continues to use its Building Block Solutions approach to deliver state-of-the-art and secure systems for the most demanding AI, Cloud, and 5G Edge requirements. The systems support high-performance CPUs and DDR5 memory with up to 2X the performance and capacities up to 512 GB DIMMs and PCIe 5.0, which doubles I/O bandwidth. Intel Xeon CPU Max Series CPUs (formerly codenamed Sapphire Rapids HBM High Bandwidth Memory (HBM)) is also available on a range of Supermicro X13 systems. In addition, support for high ambient temperature environments at up to 40° C (104° F), with servers designed for air and liquid cooling for optimal efficiency, are rack-scale optimized with open industry standard designs and improved security and manageability.

"Supermicro is once again at the forefront of delivering the broadest portfolio of systems based on the latest technology from Intel," stated Charles Liang, president and CEO of Supermicro. "Our Total IT Solutions strategy enables us to deliver a complete solution to our customers, which includes hardware, software, rack-scale testing, and liquid cooling. Our innovative platform design and architecture bring the best from the 4th Gen Intel Xeon Scalable processors, delivering maximum performance, configurability, and power savings to tackle the growing demand for performance and energy efficiency. The systems are rack-scale optimized with Supermicro's significant growth of rack-scale manufacturing of up to 3X rack capacity."

The 60th edition of the TOP500 reveals that the Frontier system is still the only true exascale machine on the list.

With an HPL score of 1.102 EFlop/s, the Frontier machine at Oak Ridge National Laboratory (ORNL) did not improve upon the score it reached on the June 2022 list. That said, Frontier's near-tripling of the HPL score received by second-place winner is still a major victory for computer science. On top of that, Frontier demonstrated a score of 7.94 EFlop/s on the HPL-MxP benchmark, which measures performance for mixed-precision calculation. Frontier is based on the HPE Cray EX235a architecture and it relies on AMD EPYC 64C 2 GHz processor. The system has 8,730,112 cores and a power efficiency rating of 52.23 gigaflops/watt. It also relies on gigabit ethernet for data transfer.

SiPearl, the company designing the highperformance, low-power microprocessor for European supercomputers, has entered into a business collaboration agreement with AMD to provide a joint offering for exascale supercomputing systems, combining SiPearl's HPC microprocessor, Rhea, with AMD Instinct accelerators.

Initially, AMD and SiPearl will jointly assess the interoperability of the AMD ROCm open software with the SiPearl Rhea microprocessor and build an optimized software solution that would strengthen the capabilities of a SiPearl microprocessor combined with an AMD Instinct accelerator. This joint work targets porting and optimization activities of the AMD HIP backend, openMP compilers and libraries, will enable scientific applications to benefit from both technologies.

Cerebras Systems, the pioneer in accelerating artificial intelligence (AI) compute, today unveiled Andromeda, a 13.5 million core AI supercomputer, now available and being used for commercial and academic work. Built with a cluster of 16 Cerebras CS-2 systems and leveraging Cerebras MemoryX and SwarmX technologies, Andromeda delivers more than 1 Exaflop of AI compute and 120 Petaflops of dense compute at 16-bit half precision. It is the only AI supercomputer to ever demonstrate near-perfect linear scaling on large language model workloads relying on simple data parallelism alone.

With more than 13.5 million AI-optimized compute cores and fed by 18,176 3rd Gen AMD EPYC processors, Andromeda features more cores than 1,953 Nvidia A100 GPUs and 1.6 times as many cores as the largest supercomputer in the world, Frontier, which has 8.7 million cores. Unlike any known GPU-based cluster, Andromeda delivers near-perfect scaling via simple data parallelism across GPT-class large language models, including GPT-3, GPT-J and GPT-NeoX.

TYAN, an industry-leading server platform design manufacturer and a MiTAC Computing Technology Corporation subsidiary, brings its upcoming server platforms powered by 4th Gen Intel Xeon Scalable processors optimized for HPC and storage markets at SC22 on November 14-17, Booth#2000 in the Kay Bailey Hutchison Convention Center Dallas.

"Greater availability of new technology like 4th Gen Intel Xeon Scalable processors continue driving the changes in the HPC landscape", said Danny Hsu, Vice President of MiTAC Computing Technology Corporation's Server Infrastructure Business Unit. "The advances in chip technology coupled with the rise in cloud computing has brought high levels of compute power within reach for smaller organizations. HPC now is affordable and accessible to a new generation of users."

Yesterday, AMD announced its latest addition to the data center family of processors called EPYC Genoa. Named the 4th generation EPYC processors, they feature a Zen 4 design and bring additional I/O connectivity like PCIe 5.0, DDR5, and CXL support. To disrupt the cloud, enterprise, and HPC offerings, AMD decided to manufacture SKUs with up to 96 cores and 192 threads, an increase from the previous generation's 64C/128T designs. Today, we are learning more about the performance and power aspects of the 4th generation AMD EPYC Genoa 9654, 9554, and 9374F SKUs from 3rd party sources, and not the official AMD presentation. Tom's Hardware published a heap of benchmarks consisting of rendering, compilation, encoding, parallel computing, molecular dynamics, and much more.

In the comparison tests, we have AMD EPYC Milan 7763, 75F3, and Intel Xeon Platinum 8380, a current top-end Intel offering until Sapphire Rapids arrives. Comparing 3rd-gen EPYC 64C/128T SKUs with 4th-gen 64C/128T EPYC SKUs, the new generation brings about a 30% increase in compression and parallel compute benchmarks performance. When scaling to the 96C/192T SKU, the gap is widened, and AMD has a clear performance leader in the server marketplace. For more details about the benchmark results, go here to explore. As far as comparison to Intel offerings, AMD leads the pack as it has a more performant single and multi-threaded design. Of course, beating the Sapphire Rapids to market is a significant win for team red, so we are still waiting to see how the 4th generation Xeon stacks up against Genoa.

Rescale, the leader in high performance computing built for the cloud to accelerate engineering innovation, today announced it is teaming with NVIDIA to integrate the NVIDIA AI platform into Rescale's HPC-as-a-Service offering. The integration is designed to advance computational engineering simulation with AI and machine learning, helping enterprises commercialize new product innovations faster, more efficiently and at less cost.

Additionally, Rescale announced the world's first Compute Recommendation Engine (CRE) to power Intelligent Computing for HPC and AI workloads. Optimizing workload performance can be prohibitively complex as organizations seek to balance decisions among architectures, geographic regions, price points, scalability, service levels, compliance, and sustainability objectives. Developed using machine learning on NVIDIA architectures with infrastructure telemetry, industry benchmarks, and full-stack metadata spanning over 100 million production HPC workloads, Rescale CRE provides customers unprecedented insight to optimize overall performance.

ASUS, a leading provider of server systems, server motherboards and workstations, today announced new best-in-class server solutions powered by the latest AMD EPYC 9004 Series processors. ASUS also launched superior liquid-cooling solutions that dramatically improve the data-center power-usage effectiveness (PUE).

The breakthrough thermal design in this new generation delivers superior power and thermal capabilities to support class-leading features, including up to 400-watt CPUs, up to 350-watt GPUs, and 400 Gbps networking. All ASUS liquid-cooling solutions will be demonstrated in the ASUS booth (number 3816) at SC22 from November 14-17, 2022, at Kay Bailey Hutchison Convention Center in Dallas, Texas.

Hewlett Packard Enterprise (NYSE: HPE) today announced it is making supercomputing accessible for more enterprises to harness insights, solve problems and innovate faster by delivering its world-leading, energy-efficient supercomputers in a smaller form factor and at a lower price point.

The expanded portfolio includes new HPE Cray EX and HPE Cray XD supercomputers, which are based on HPE's exascale innovation that delivers end-to-end, purpose-built technologies in compute, accelerated compute, interconnect, storage, software, and flexible power and cooling options. The supercomputers provide significant performance and AI-at-scale capabilities to tackle demanding, data-intensive workloads, speed up AI and machine learning initiatives, and accelerate innovation to deliver products and services to market faster.

TSMC today announced the Open Innovation Platform (OIP) 3DFabric Alliance at the 2022 Open Innovation Platform Ecosystem Forum. The new TSMC 3DFabric Alliance is TSMC's sixth OIP Alliance and the first of its kind in the semiconductor industry that joins forces with partners to accelerate 3D IC ecosystem innovation and readiness, with a full spectrum of best-in-class solutions and services for semiconductor design, memory modules, substrate technology, testing, manufacturing, and packaging. This alliance will help customers achieve speedy implementation of silicon and system-level innovations and enable next-generation HPC and mobile applications using TSMC's 3DFabric technologies, a comprehensive family of 3D silicon stacking and advanced packaging technologies.

"3D silicon stacking and advanced packaging technologies open the door to a new era of chip-level and system-level innovation, and also require extensive ecosystem collaboration to help designers navigate the best path through the myriad options and approaches available to them," said Dr. L.C. Lu, TSMC fellow and vice president of design and technology platform. "Through the collective leadership of TSMC and our ecosystem partners, our 3DFabric Alliance offers customers an easy and flexible way to unlocking the power of 3D IC in their designs, and we can't wait to see the innovations they can create with our 3DFabric technologies."

Alphawave IP (LSE: AWE), a global leader in high-speed connectivity for the world's technology infrastructure, today announced the successful tapeout of its ZeusCORE100 1-112 Gbps NRZ/PAM4 Serialiser-Deserialiser ("SerDes"), Alphawave's first testchip on TSMC's most advanced N3E process. Alphawave IP will be exhibiting this new product alongside its complete portfolio of high-performance IP, chiplet, and custom silicon solutions at the TSMC OIP Forum on October 26 in Santa Clara, CA as the Platinum sponsor.

ZeusCORE100 is Alphawave's most advanced multi-standard-SerDes, supporting extra-long channels over 45dB and the most requested standards such as 800G Ethernet, OIF 112G-CEI, PCIe GEN6, and CXL 3.0. Attendees will be able to visit the Alphawave booth and meet the company's technology experts including members of the recently acquired OpenFive team. OpenFive is a longstanding partner of TSMC through the OIP Value Chain Aggregator (VCA) program. OpenFive is one of a select few companies with an idea-to-silicon methodology in TSMC's latest technologies, and advanced packaging capabilities, enabling access to the most advanced foundry solution available with the best Power-Performance-Area (PPA). With Alphawave's industry-leading IP portfolio and the addition of OpenFive's capabilities, designers can create systems on a chip (SoCs) that pack more compute power into smaller form factors for networking, AI, storage, and high-performance computing (HPC) applications.

According to the latest TrendForce research, pandemic-induced materials shortages abated in the second half of this year and the supply and delivery of short-term materials has recovered significantly. However, assuming materials supply is secure and demand can be met, the annual growth rate of server shipments in 2023 is estimated to be only 3.7%, which is lower than 5.1% in 2022.

TrendForce indicates that this growth slowdown is due to three factors. First, once material mismatch issues had eased, buyers began adjusting previously placed purchase order overruns. Thus, ODM orders also decreased but this will not affect the 2022 shipment volume of whole servers for the time being. Second, due to the impact of rising inflation and weakness in the overall economy, corporate capital investment may trend more conservative and IT-related investment will emphasize flexibility, such as the replacement of certain server terminals with cloud services. Third, geopolitical changes will drive the continuing emergence of demand for small-scale data centers and previous construction of hyperscale data centers will slow. The recent ban on military/HPC servers issued by the U.S. Department of Commerce on October 7 has a very low market share in terms of its application category, so the impact on the overall server market is limited at present. However, if the scope of the ban is expanded further in the future, it will herald a more significant slowdown risk for China's server shipment momentum in 2023.

When AMD announced that the company would deliver the world's fastest supercomputer, Frontier, the company also took a massive task to provide a machine capable of producing one ExaFLOP of total sustained ability to perform computing tasks. While the system is finally up and running, making a machine of that size run properly is challenging. In the world of High-Performance Computing, getting the hardware is only a portion of running the HPC center. In an interview with InsideHPC, Justin Whitt, program director for the Oak Ridge Leadership Computing Facility (OLCF), provided insight into what it is like to run the world's fastest supercomputer and what kinds of issues it is facing.

The Frontier system is powered by AMD EPYC 7A53s "Trento" 64-core 2.0 GHz CPUs and Instinct MI250X GPUs. Interconnecting everything is the HPE (Cray) Slingshot 64-port switch, which is responsible for sending data in and out of compute blades. The recent interview points out a rather interesting finding: exactly AMD Instinct MI250X GPUs and Slingshot interconnect cause hardware troubles for the Frontier. "It's mostly issues of scale coupled with the breadth of applications, so the issues we're encountering mostly relate to running very, very large jobs using the entire system … and getting all the hardware to work in concert to do that," says Justin Whitt. In addition to the limits of scale "The issues span lots of different categories, the GPUs are just one. A lot of challenges are focused around those, but that's not the majority of the challenges that we're seeing," he said. "It's a pretty good spread among common culprits of parts failures that have been a big part of it. I don't think that at this point that we have a lot of concern over the AMD products. We're dealing with a lot of the early-life kind of things we've seen with other machines that we've deployed, so it's nothing too out of the ordinary."

Samsung Electronics, a world leader in advanced semiconductor technology, announced today a strengthened business strategy for its Foundry Business with the introduction of cutting-edge technologies at its annual Samsung Foundry Forum event. With significant market growth in high-performance computing (HPC), artificial intelligence (AI), 5/6G connectivity and automotive applications, demand for advanced semiconductors has increased dramatically, making innovation in semiconductor process technology critical to the business success of foundry customers. To that end, Samsung highlighted its commitment to bringing its most advanced process technology, 1.4-nanometer (nm), for mass production in 2027.

During the event, Samsung also outlined steps its Foundry Business is taking in order to meet customers' needs, including: foundry process technology innovation, process technology optimization for each specific applications, stable production capabilities, and customized services for customers. "The technology development goal down to 1.4 nm and foundry platforms specialized for each application, together with stable supply through consistent investment are all part of Samsung's strategies to secure customers' trust and support their success," said Dr. Si-young Choi, president and head of Foundry Business at Samsung Electronics. "Realizing every customer's innovations with our partners has been at the core of our foundry service."

DFI, the world's leading brand in embedded motherboards and industrial computers, was invited to participate in "AMD Datacenter Solutions Day" in September, based on the theme of high-performance computing (HPC). As the first in the world to launch the smallest industrial motherboard equipped with AMD products, DFI partnered with its subsidiary, AEWIN, to present their star products and share how ultra-small products can help the trend of software virtualization technologies in the forum. We hope to optimize the development of diverse services in IoT applications.

AMD invited industry giants to the event to discuss the future of high-performance computing and conduct in-depth discussions with their partners related to high-performance computing, cloud computing, and AI. DFI was a speaker in the digital learning AI session during the event. DFI shared their views on software-defined IoT and explained the role of ultra-small products in the application environment.

According to TrendForce research, due to steady weakening of overall demand for consumer electronics, inventory pressure has increased among downstream distributors and brands. Although there are still sporadic shortages of specific components, the curtain has officially fallen on a two-year wave of shortages in general, and brands have gradually suspended stocking in response to changes in market conditions. However, stable demand for automotive and industrial equipment is key to supporting the ongoing growth of foundry output value. At the same time, since the creation of a marginal amount of new capacity in 2Q22 led to growth in wafer shipments and a price hike for certain wafers, this drove output value among top ten foundries to reach US$33.20 billion in 2Q22. Quarterly growth fell to 3.9% on a weakening consumer market.

A prelude to inventory correction was officially revealed in 3Q22. In addition to intensifying severity in the initial wave of order slashing for LDDI/TDDI, and TV SoC, diminishing order volume also extended to non-Apple smartphone APs and peripheral IC PMIC, CIS, and consumer electronics PMICs, and mid-to-low-end MCUs, posing a challenge for foundry capacity utilization. However, the launch of the new iPhone in 3Q22 is expected to prop up a certain amount of stocking momentum for the sluggish market. Therefore, top ten foundry revenue in 3Q22 is expected to maintain a growth trend driven by high-priced processes and quarterly growth rate is expected to be slightly higher than in 2Q22.

NVIDIA's high-performance computing hardware stack is now equipped with the top-of-the-line Hopper H100 GPU. It features 16896 or 14592 CUDA cores, developing if it comes in SXM5 of PCIe variant, with the former being more powerful. Both variants come with a 5120-bit interface, with the SXM5 version using HBM3 memory running at 3.0 Gbps speed and the PCIe version using HBM2E memory running at 2.0 Gbps. Both versions use the same capacity capped at 80 GBs. However, that could soon change with the latest rumor suggesting that NVIDIA could be preparing a PCIe version of Hopper H100 GPU with 120 GBs of an unknown type of memory installed.

According to the Chinese website "s-ss.cc" the 120 GB variant of the H100 PCIe card will feature an entire GH100 chip with everything unlocked. As the site suggests, this version will improve memory capacity and performance over the regular H100 PCIe SKU. With HPC workloads increasing in size and complexity, more significant memory allocation is needed for better performance. With the recent advances in Large Language Models (LLMs), AI workloads use trillions of parameters for tranining, most of which is done on GPUs like NVIDIA H100.

During its GTC 2022 session, NVIDIA introduced its new generation of gaming graphics cards based on the novel Ada Lovelace architecture. Dubbed NVIDIA GeForce RTX 40 series, it brings various updates like more CUDA cores, a new DLSS 3 version, 4th generation Tensor cores, 3rd generation Ray Tracing cores, and much more, which you can read about here. However, today, we also got a new Ada Lovelace card intended for the data center. Called the L40, NVIDIA updated its previous Ampere-based A40 design. While the NVIDIA website provides sparse, the new L40 GPU uses 48 GB GDDR6 memory with ECC error correction. Using NVLink, you can get 96GBs of VRAM. Paired with an unknown SKU, we assume that it uses AD102 with adjusted frequencies to lower the TDP and allow for passive cooling.

NVIDIA is calling this their Omniverse GPU, as it is a part of the push to separate its GPUs used for graphics and AI/HPC models. The "L" model in the current product stack is used to accelerate graphics, with display ports installed on the GPU, while the "H" models (H100) are there to accelerate HPC/AI installments where visual elements are a secondary task. This is a further separation of the entire GPU market, where the HPC/AI SKUs get their own architecture, and GPUs for graphics processing are built on a new architecture as well. You can see the specifications provided by NVIDIA below.

Yesterday, NVIDIA launched its GeForce RTX 40-series, based on the "Ada" graphics architecture. We're yet to receive a technical briefing about the architecture itself, and the various hardware components that make up the silicon; but NVIDIA on its website gave us a first look at what's in store with the key number-crunching components of "Ada," namely the Ada CUDA core, 4th generation Tensor core, and 3rd generation RT core. Besides generational IPC and clock speed improvements, the latest CUDA core benefits from SER (shader execution reordering), an SM or GPC-level feature that reorders execution waves/threads to optimally load each CUDA core and improve parallelism.

Despite using specialized hardware such as the RT cores, the ray tracing pipeline still relies on CUDA cores and the CPU for a handful tasks, and here NVIDIA claims that SER contributes to a 3X ray tracing performance uplift (the performance contribution of CUDA cores). With traditional raster graphics, SER contributes a meaty 25% performance uplift. With Ada, NVIDIA is introducing its 4th generation of Tensor core (after Volta, Turing, and Ampere). The Tensor cores deployed on Ada are functionally identical to the ones on the Hopper H100 Tensor Core HPC processor, featuring the new FP8 Transformer Engine, which delivers up to 5X the AI inference performance over the previous generation Ampere Tensor Core (which itself delivered a similar leap by leveraging sparsity).

The demand for data is insatiable, from 5G to the cloud to smart cities. As a society we want more autonomy, information to fuel our decisions and habits, and connection - to people, stories, and experiences.

To address these demands, the cloud infrastructure of tomorrow will need to handle the coming data explosion and the effective processing of evermore complex workloads … all while increasing power efficiency and minimizing carbon footprint. It's why the industry is increasingly looking to the performance, power efficiency, specialized processing and workload acceleration enabled by Arm Neoverse to redefine and transform the world's computing infrastructure.

AMD today announced it is joining the newly created PyTorch Foundation as a founding member. The foundation, which will be part of the non-profit Linux Foundation, will drive adoption of Artificial Intelligence (AI) tooling by fostering and sustaining an ecosystem of open source projects with PyTorch, the Machine Learning (ML) software framework originally created and fostered by Meta.

As a founding member, AMD joins others in the industry to prioritize the continued growth of PyTorch's vibrant community. Supported by innovations such as the AMD ROCm open software platform, AMD Instinct accelerators, Adaptive SoCs and CPUs, AMD will help the PyTorch Foundation by working to democratize state-of-the-art tools, libraries and other components to make these ML innovations accessible to everyone.

With its recent announcement of the Ryzen 7000 desktop processors, the action now shifts to the server, with AMD preparing a wide launch of its EPYC "Genoa" and "Bergamo" processors this year. Powered by the "Zen 4" microarchitecture, and contemporary I/O that includes PCI-Express Gen 5, CXL, and DDR5, these processors dial the CPU core-counts per socket up to 96 in case of "Genoa," and up to 128 in case of "Bergamo." The EPYC "Genoa" series represents the main trunk of the company's server processor lineup, with various internal configurations targeting specific use-cases.

The 96 cores are spread twelve 5 nm 8-core CCDs, each with a high-bandwidth Infinity Fabric path to the sIOD (server I/O die), which is very likely built on the 6 nm node. Lower core-count models can be built either by lowering the CCD count (ensuring more cores/CCD), or by reducing the number of cores/CCD and keeping the CCD-count constant, to yield more bandwidth/core. The leaked product-stack table below shows several of these sub-classes of "Genoa" and "Bergamo," classified by use-cases. The leaked slide also details the nomenclature AMD is using with its new processors. The leaked roadmap also mentions the upcoming "Genoa-X" processor for HPC and cloud-compute uses, which features the 3D Vertical Cache technology.

Ansys announced that Ansys Mechanical is one of the first commercial finite element analysis (FEA) programs supporting AMD Instinct accelerators, the newest data center GPUs from AMD. The AMD Instinct accelerators are designed to provide exceptional performance for data centers and supercomputers to help solve the world's most complex problems. To support the AMD Instinct accelerators, Ansys developed APDL code in Ansys Mechanical to interface with AMD ROCm libraries on Linux, which will support performance and scaling on the AMD accelerators.

Ansys' latest collaboration with AMD resulted in a solution that, according to Ansys' tests, significantly speeds up simulation of large structural mechanical models—between three and six times faster for Ansys Mechanical applications using the sparse direct solver. Adding support for AMD Instinct accelerators in Ansys Mechanical gives customers greater flexibility in their choice of high-performance computing (HPC) hardware.

Intel today launched its Arctic Sound M line of data-center GPUs. These are not positioned as HPC processors like the "Ponte Vecchio," but GPUs targeting cloud-compute providers, with their main applications being in the realm of visual processing, media, and AI inferencing. Their most interesting aspect has to be the silicon, which are the same 6 nm "ACM-G11" and "ACM-G10" chips powering the Arc "Alchemist" client graphics cards, based on the Xe-HPG architecture. Even more interesting is their typical board power values, ranging between 75 W to 150 W. The cards are built in the PCI-Express add-on card form-factor, with their cooling solutions optimized for rack airflow.

The marketing name for these cards is simply Intel Data Center GPU Flex, with two models being offered: The Data Center GPU Flex-140, and Flex-170. The Flex-170 is a full-sized add-on card based on the larger ACM-G10 silicon, which has 32 Xe Cores (4,096 unified shaders), whereas the Flex-140, interestingly, is a low-profile dual-GPU card with two smaller ACM-G11 chips that each has 8 Xe Cores (1,024 unified shaders). The two chips appear to be sharing a PCIe bridge chip in the renders. Both models come with four Xe Media Engines that pack AV1 encode hardware-acceleration, XMX AI acceleration, real-time ray tracing, and GDDR6 memory.