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).

NVIDIA today expanded the NVIDIA Jetson lineup with the launch of new Jetson Orin Nano system-on-modules that deliver up to 80x the performance over the prior generation, setting a new standard for entry-level edge AI and robotics. For the first time, the NVIDIA Jetson family spans six Orin-based production modules to support a full range of edge AI and robotics applications. This includes the Orin Nano—which delivers up to 40 trillion operations per second (TOPS) of AI performance in the smallest Jetson form factor—up to the AGX Orin, delivering 275 TOPS for advanced autonomous machines.

Jetson Orin features an NVIDIA Ampere architecture GPU, Arm-based CPUs, next-generation deep learning and vision accelerators, high-speed interfaces, fast memory bandwidth and multimodal sensor support. This performance and versatility empower more customers to commercialize products that once seemed impossible, from engineers deploying edge AI applications to Robotics Operating System (ROS) developers building next-generation intelligent machines.

NVIDIA's upcoming GeForce RTX 4080 "Ada," a successor to the RTX 3080 "Ampere," reportedly comes in two distinct variants based on memory size, memory bus width, and possibly even core-configuration. MEGAsizeGPU reports that they have seen two reference designs for the RTX 4080, one with 12 GB of memory and a 10-layer PCB, and the other with 16 GB of memory and a 12-layer PCB. Increasing numbers of PCB layers enable greater density of wiring around the ASIC. At debut, the flagship product from NVIDIA is expected to be the RTX 4090, with its 24 GB memory size, and 14-layer PCB. Apparently, the 12 GB and 16 GB variants of the RTX 4080 feature vastly different PCB designs.

We've known from past attempts at memory-based variants, such as the GTX 1060 (3 GB vs. 6 GB), or the more recent RTX 3080 (10 GB vs. 12 GB), that NVIDIA turns to other levers to differentiate variants, such as core-configuration (numbers of available CUDA cores), and the same is highly likely with the RTX 4080. The RTX 4080 12 GB, RTX 4080 16 GB, and the RTX 4090, could be NVIDIA's answers to AMD's RDNA3-based successors of the RX 6800, RX 6800 XT, and RX 6950 XT, respectively.

NVIDIA in its HotChips 34 presentation revealed a defining feature of its "Hopper" compute architecture that works to increase parallelism and help the H100 processor better perform in a multi-instance environment. The hardware component hierarchy of "Hopper" is typical of NVIDIA architectures, with GPCs, SMs, and CUDA cores forming a hierarchy. The company is introducing a new component it calls "SM to SM Network." This is a high-bandwidth communications fabric inside the Graphics Processing Cluster (GPC), which facilitates direct communication among the SMs without making round-trips to the cache or memory hierarchy, play a significant role in NVIDIA's overarching claim of "6x throughput gain over the A100."

Direct SM-to-SM communication not just impacts latency, but also unburdens the L2 cache, letting NVIDIA's memory-management free up the cache of "cooler" (infrequently accessed) data. CUDA sees every GPU as a "grid," every GPC as a "Cluster," every SM as a "thread block," and every lane of SIMD units as a "lane." Each lane has a 64 KB of shared memory, which makes up 256 KB of shared local storage per SM as there are four lanes. The GPCs interface with 50 MB of L2 cache, which is the last-level on-die cache before the 80 GB of HBM3 serves as main memory.

Bringing new AI and robotics applications and products to market, or supporting existing ones, can be challenging for developers and enterprises. The NVIDIA Jetson AGX Orin 32 GB production module—available now—is here to help. Nearly three dozen technology providers in the NVIDIA Partner Network worldwide are offering commercially available products powered by the new module, which provides up to a 6x performance leap over the previous generation.

With a wide range of offerings from Jetson partners, developers can build and deploy feature-packed Orin-powered systems sporting cameras, sensors, software and connectivity suited for edge AI, robotics, AIoT and embedded applications. Production-ready systems with options for peripherals enable customers to tackle challenges in industries from manufacturing, retail and construction to agriculture, logistics, healthcare, smart cities, last-mile delivery and more.

NVIDIA's upcoming GeForce RTX 40 series Ada Lovelace graphics card lineup is slowly shaping up to be a significant performance uplift compared to the previous generation. Today, according to a well-known hardware leaker kopite7kimi, we are speculating that a mid-range AD104 SKU could match the performance of the last-generation flagship GeForce RTX 3090 Ti graphics card. The full AD104 SKU is set to feature 7680 FP32 CUDA cores, paired with 12 GB of 21 Gbps GDDR6X memory running on a 192-bit bus. Coming with a large TGP of 400 Watts, it should have a performance of the GA102-350-A1 SKU found in GeForce RTX 3090 Ti.

Regarding naming this complete AD104 SKU, it should end up as a GeForce RTX 4070 Ti model. Of course, we must wait and see what NVIDIA decides to do with the lineup and what the final models will look like.

NVIDIA's next-generation GeForce RTX 40 series of graphics cards, codenamed Ada Lovelace, is shaping up to be a powerful graphics card lineup. Allegedly, we can expect to see a mid-July launch of NVIDIA's newest gaming offerings, where customers can expect some impressive performance. According to a reliable hardware leaker, kopite7kimi, NVIDIA GeForce RTX 4090 graphics card will feature AD102-300 GPU SKU. This model is equipped with 126 Streaming Multiprocessors (SMs), which brings the total number of FP32 CUDA cores to 16128. Compared to the full AD102 GPU with 144 SMs, this leads us to think that there will be an RTX 4090 Ti model following up later as well.

Paired with 24 GB of 21 Gbps GDDR6X memory, the RTX 4090 graphics card has a TDP of 450 Watts. While this number may appear as a very power-hungry design, bear in mind that the targeted performance improvement over the previous RTX 3090 model is expected to be a two-fold scale. Paired with TSMC's new N4 node and new architecture design, performance scaling should follow at the cost of higher TDPs. These claims are yet to be validated by real-world benchmarks of independent tech media, so please take all of this information with a grain of salt and wait for TechPowerUp reviews once the card arrives.

Chinese company Moore Threads has unveiled their MTT GPU series just 18 months after the company's establishment in 2020. The MT Unified System Architecture (MUSA) architecture is the first for any Chinese company to be developed fully domestically and includes support for DirectX, OpenCL, OpenGL, Vulkan, and CUDA. The company announced the MTT S60 and MTT S2000 single slot desktop graphics cards for gaming and server applications at a recent event. The MTT S60 is manufactured on a 12 nm node and features 2,048 MUSA cores paired with 8 GB of LPGDDR4X memory offering 6 TFLOPs of performance. The MTT S2000 is also manufactured on a 12 nm node and doubles the number of MUSA cores to 4096 paired with 32 GB of undisclosed video memory allowing it to reach 12 TFLOPs.

Moore Threads joins Intel in supporting AV1 encoding on a consumer GPU with MUSA cards featuring H.264, H.265, and AV1 encoding support in addition to H.264, H.265, AV1, VP8, and VP9 decoding. The company is also developing a physics engine dubbed Alphacore which is said to work with existing tools such as Unity, Unreal Engine, and Houdini to accelerate physics performance by 5 to 10 times. The only gaming performance shown was a simple demonstration of the MTT S60 running League of Legends at 1080p without any frame rate details.

With the announcement of the NVIDIA Jetson AGX Orin developer kit, AAEON is excited to utilize the many benefits that such a powerful system-on-module (SOM) can bring to its own product lines. With the same form factor and pin compatibility as the NVIDIA Jetson AGX Xavier, but with an improvement from 32 TOPS to 275 TOPS, the NVIDIA Jetson AGX Orin is set to make it easier than ever to develop faster, more sophisticated AI applications.

AAEON is therefore pleased to announce two upcoming products available in Q4 which will feature the Jetson AGX Orin 32 GB and Jetson AGX Orin 64 GB as their respective processor modules: the BOXER-8260AI and BOXER-8261 AI@Edge Embedded BOX PCs. Both products will feature the NVIDIA JetPack 5.0 SDK to support the full Jetson software stack to help in the development of AI applications in areas such as high-end autonomous machinery. With two NVIDIA deep learning accelerators (NVDLA), along with a 32 GB 256-bit system memory, the BOXER-8260AI will provide the perfect device for vision-based AI applications. Moreover, its expansive I/O options include 12 RJ-45 slots for PoE, along with DB-9 slots for CANbus and six DIO.

During the GTC 2022 keynote, NVIDIA announced its newest addition to the accelerator cards family. Called NVIDIA H100 accelerator, it is the company's most powerful creation ever. Utilizing 80 billion of TSMC's 4N 4 nm transistors, H100 can output some insane performance, according to NVIDIA. Featuring a new fourth-generation Tensor Core design, it can deliver a six-fold performance increase compared to A100 Tensor Cores and a two-fold MMA (Matrix Multiply Accumulate) improvement. Additionally, new DPX instructions accelerate Dynamic Programming algorithms up to seven times over the previous A100 accelerator. Thanks to the new Hopper architecture, the Streaming Module structure has been optimized for better transfer of large data blocks.

The full GH100 chip implementation features 144 SMs, and 128 FP32 CUDA cores per SM, resulting in 18,432 CUDA cores at maximum configuration. The NVIDIA H100 GPU with SXM5 board form-factor features 132 SMs, totaling 16,896 CUDA cores, while the PCIe 5.0 add-in card has 114 SMs, totaling 14,592 CUDA cores. As much as 80 GB of HBM3 memory surrounds the GPU at 3 TB/s bandwidth. Interestingly, the SXM5 variant features a very large TDP of 700 Watts, while the PCIe card is limited to 350 Watts. This is the result of better cooling solutions offered for the SXM form-factor. As far as performance figures are concerned, the SXM and PCIe versions provide two distinctive figures for each implementation. You can check out the performance estimates in various precision modes below. You can read more about the Hopper architecture and what makes it special in this whitepaper published by NVIDIA.

Possible streaming multiprocessor (SM) counts of the various NVIDIA "Ada Lovelace" client-graphics GPUs surfaced, allegedly pieced together from code seen in the recent NVIDIA cyberattack data-leak. According to this, the top-dog "AD102" silicon has 144 SM, the next-best "AD103" has 84. The third-largest "AD104" silicon has 60. The performance-segment "AD106" has 36, and the mainstream "AD107" has 24. Assuming the number of CUDA cores per SM in the "Ada Lovelace" graphics architecture is unchanged from that of "Ampere," we're looking at 18,432 CUDA cores for the "AD102," an impressive 10,752 for the "AD103," 7,680 cores for the "AD104," 4,608 for the "AD106," and 3,072 for the "AD107."

When NVIDIA announced the appearance of the GeForce RTX 3080 Ti mobile graphics card, we were left with a desire to see just what the GA103 silicon powering the GPU looks like. And thanks to the Chinese YouTuber Geekerwan, we have the first pictures of the GPU. Pictured below is GA103S/GA103M SKU with GN20-E8-A1 labeling. It features 58 SMs that make up for 7424 CUDA cores in total. The number of Tensor cores for this SKU is set to 232, while there are 58 RT cores. NVIDIA has decided to pair this GPU with a 256-bit memory bus and 16 GB GDDR6 memory.

As it turns out, the full GA103 silicon has a total of 7680 CUDA cores and a 320-bit memory bus, so this mobile version is a slightly cut-down variant. It sits perfectly between GA104 and GA102 SKUs, providing a significant improvement to the core count of GA104 silicon. Power consumption of the GA103 SKU for GeForce RTX 3080 Ti mobile is set to a variable 80-150 Watt range, which can be adjusted according to the system's cooling capacity. An interesting thing to point out is a die size of 496 mm², which is a quarter more significant compared to GA104, for a quarter higher number of CUDA cores.

During the CES 2022 keynote, we have witnessed NVIDIA update its GeForce RTX 30 series family with GeForce RTX 3050 and RTX 3090 Ti. However, this is not an end to NVIDIA's updates to the Ampere generation, as we now hear industry sources from Wccftech suggest that we could see a GeForce RTX 3080 GPU with 12 GB of GDDR6X VRAM enabled, launched as a separate product. Compared to the regular RTX 3080 that carries only 10 GB of GDDR6X, the new 12 GB version is supposed to bring a slight bump up to the specification list. The GA102-220 GPU SKU found inside the 12 GB variant will feature 70 SMs with 8960 CUDA, 70 RT cores, and 280 TMUs.

This represents a minor improvement over the regular GA102-200 silicon inside the 8 GB model. However, the significant difference is the memory organization. With the new 12 GB model, we have a 384-bit memory bus allowing GDDR6X modules to achieve a bandwidth of 912 GB/s, all while running at 19 Gbps speeds. The overall TDP will also receive a bump to 350 Watts, compared to 320 Watts of the regular RTX 3080 model. For more information regarding final clock speeds and pricing, we have to wait for the alleged launch date - January 11th.

NVIDIA is preparing to launch an ultimate solution for high-end laptops and gamers that could benefit from the high-performance graphics card integration in mobile systems like gaming laptops. Rumored to launch sometime in January, NVIDIA is preparing a GeForce RTX 3080 Ti mobile GPU SKU that supposedly offers the highest performance in the Ampere mobile family. According to sources close to VideoCardz, team green has prepared to announce RTX 3080 Ti mobile design with faster memory and higher total graphics power (TGP). The memory speed will get an upgrade to 16 Gbps, compared to the 14 Gbps speed in RTX 3080 mobile SKU.

Similarly, the total overall TGP will also receive a bump to 175 Watts. This is just a tad higher than the 165 Watt TGP of RTX 3080 mobile. The Ti version will upgrade the CUDA core count and other things like TMUs to undetermined specifications. Currently, it is rumored that the Ti version could carry 7424 CUDA cores, which is an upgrade from 6144 of the regular RTX 3080 version.

In the past few months, we have heard rumors of NVIDIA launching an upgraded version of the GA102 silicon called GeForce RTX 3090 Ti. The upgraded version is supposed to max out the chip and bring additional performance to the table. According to anonymous sources of VideoCardz, MSI, one of NVIDIA's add-in board (AIB) partners, is preparing to update its SUPRIM X lineup of graphics cards with the MSI GeForce RTX 3090 Ti SUPRIM X GPU, scheduled for January 27th launch date. This suggests that the official NDA lifts for these RTX 3090 Ti GPUs on January 27th, meaning that we could see AIBs teasing their models very soon.

As a general reminder, the GeForce RTX 3090 Ti graphics card should use a GA102-350 silicon SKU with 84 SMs, 10752 CUDA cores, 336 TMUs, 24 GB of GDDR6X memory running on a 384-bit bus at 21 Gbps speed with 1008 GB/s bandwidth, and a TBP of a whopping 450 Watts. If these specifications remain valid, the GPU could become the top contender in the market, however, with a massive drawback of pulling nearly half a KiloWatt of power.

Intel today released oneAPI 2022 toolkits. Newly enhanced toolkits expand cross-architecture features to provide developers greater utility and architectural choice to accelerate computing. "I am impressed by the breadth of more than 900 technical improvements that the oneAPI software engineering team has done to accelerate development time and performance for critical application workloads across Intel's client and server CPUs and GPUs. The rich set of oneAPI technologies conforms to key industry standards, with deep technical innovations that enable applications developers to obtain the best possible run-time performance from the cloud to the edge. Multi-language support and cross-architecture performance acceleration are ready today in our oneAPI 2022 release to further enable programmer productivity on Intel platforms," said Greg Lavender, Intel chief technology officer, senior vice president and general manager of the Software and Advanced Technology Group.

New capabilities include the world's first unified compiler implementing C++, SYCL and Fortran, data parallel Python for CPUs and GPUs, advanced accelerator performance modeling and tuning, and performance acceleration for AI and ray tracing visualization workloads. The oneAPI cross-architecture programming model provides developers with tools that aim to improve the productivity and velocity of code development when building cross-architecture applications.

NVIDIA's Crypto Mining (CMP) series of graphics cards are made to work only for one purpose: mining cryptocurrency coins. Hence, their functionality is somewhat limited, and they can not be used for gaming as regular GPUs can. Today, Linus Tech Tips got ahold of NVIDIA's CMP 170HX mining card, which is not listed on the company website. According to the source, the card runs on NVIDIA's GA100-105F GPU, a version based on the regular GA100 SXM design used in data-center applications. Unlike its bigger brother, the GA100-105F SKU is a cut-down design with 4480 CUDA cores and 8 GB of HBM2E memory. The complete design has 6912 cores and 40/80 GB HBM2E memory configurations.

As far as the reason for choosing 8 GB HBM2E memory goes, we know that the Ethereum DAG file is under 5 GB, so the 8 GB memory buffer is sufficient for mining any coin out there. It is powered by an 8-pin CPU power connector and draws about 250 Watts of power. It can be adjusted to 200 Watts while retaining the 165 MH/s hash rate for Ethereum. This reference design is manufactured by NVIDIA and has no active cooling, as it is meant to be cooled in high-density server racks. Only a colossal heatsink is attached, meaning that the cooling needs to come from a third party. As far as pricing is concerned, Linus managed to get this card for $5000, making it a costly mining option.More images follow...

Xiaomi today took another bold step in the exploration of future technology with its new bio-inspired quadruped robot - CyberDog. The launch of CyberDog is the culmination of Xiaomi's engineering prowess, condensed into an open source robot companion that developers can build upon.

CyberDog is Xiaomi's first foray into quadruped robotics for the open source community and developers worldwide. Robotics enthusiasts interested in CyberDog can compete or co-create with other like-minded Xiaomi Fans, together propelling the development and potential of quadruped robots.

NVIDIA's upcoming "Ada Lovelace" architecture, both for compute and graphics, is reportedly being designed for the 5 nanometer silicon fabrication node by TSMC. This marks NVIDIA's return to the Taiwanese foundry after its brief excursion to Samsung, with the 8 nm "Ampere" graphics architecture. "Ampere" compute dies continue to be built on TSMC 7 nm nodes. NVIDIA is looking to double the compute performance on its next-generation GPUs, with throughput approaching 70 TFLOP/s, from a numeric near-doubling in CUDA cores, generation-over-generation. These will also be run at clock speeds above 2 GHz. One can expect "Ada Lovelace" only by 2022, as TSMC N5 matures.

When NVIDIA's Ampere GPUs first stormed onto the scene, the GeForce RTX 3090 created an entirely new category of performance for the highest-resolution, highest-refresh-rate graphics and most demanding GPU compute tasks on the market. Now, the GeForce RTX 3080 Ti brings much of the power of that revolutionary graphics card to a wider audience. The RTX 3080 Ti's massive complement of CUDA, RT, and Tensor cores teams up with 12 GB of GDDR6X memory to create a potent package that's tailored for gamers first. And in the hotly contested midrange of the market, the RTX 3070 Ti brings more CUDA, RT, and Tensor cores to bear for mainstream systems.

ASUS has taken advantage of these new, more powerful GPUs to create custom designs that serve up high clock speeds, low temperatures, and whisper-quiet noise levels. The ROG Strix LC GeForce RTX 3080 Ti is our first Ampere card to use a hybrid liquid-cooled design for incredible performance potential, while ROG Strix and TUF Gaming versions of both the RTX 3080 Ti and RTX 3070 Ti deliver distinctly different takes on air cooling.

ZOTAC Technology Limited, a global manufacturer of innovation, unveils two mighty additions to the ZOTAC GAMING GeForce RTX 30 Series GPU line-up-the GeForce RTX 3080 Ti and 3070 Ti Series. The all-new series are based on thea dvanced NVIDIA Ampere architecture with enhanced CUDA cores, Tensor cores, fast memory, and wide memory bandwidth that bring powerful gaming performance.

The RTX 3080 Ti Series feature the AMP Extreme Holo, AMP Holo, Trinity OC and Trinity models whereas the RTX 3070 Ti Series feature the AMP Extreme Holo, AMP Holo and Trinity. Powered by the NVIDIA Ampere architecture, the GeForce RTX 3080 Ti delivers an incredible leap in performance and fidelity with acclaimed features such as raytracing, NVIDIA DLSS performance-boosting AI, NVIDIA Reflex latency-reduction, NVIDIA Broadcast streaming features and additional memory that allows it to speed through the most popular creator applications as well.

The launch of NVIDIA's upcoming GeForce RTX 3080 Ti graphics card is upon us. The number of rumors circulating the web is getting greater and we have just received die pictures of the GA102 silicon and the specification of the specific SKU. Sources over at VideoCardz have provided the website with the first die picture of GA102-225 silicon, which powers the NVIDIA GeForce RTX 3080 Ti graphics card. Pictured below, it doesn't appear much different compared to the GA102-300 SKU found inside the RTX 3090 card, with the only obvious differentiator being the SKU ID. However, the difference only appears under the hood, with the GA102-225 SKU having 10240 CUDA cores instead of 10752 CUDA cores found inside GA102-300 of RTX 3090.

Paired with 12 GB of GDDR6X memory on a 384-bit bus, the memory will have run around 19 Gbps speeds. That will result in a bandwidth of 912 GB/s. If you are wondering about the performance of the card, it should remain within a few percent of its bigger brother RTX 3090. We have the first leak showing Ethereum mining performance and the GA102-225 silicon achieved a mining hash rate of 118.9 Mh/s with some tuning. The memory was overclocked to 21.5 Gbps, while the GPU TDP was limited to 278 Watts. The leak shows that the card has managed to achieve a 1365 MHz base and 1665 MHz boost frequency. While we don't have the exact launch date, the supposed MSRP will be anywhere from $999 to $1099, assuming you can get it at all at any price.

NVIDIA today announced a range of eight new NVIDIA Ampere architecture GPUs for next-generation laptops, desktops and servers that make it possible for professionals to work from wherever they choose, without sacrificing quality or time. For desktops, the new NVIDIA RTX A5000 and NVIDIA RTX A4000 GPUs feature new RT Cores, Tensor Cores and CUDA cores to speed AI, graphics and real-time rendering up to 2x faster than previous generations. For professionals on the go needing thin and light devices, the new NVIDIA RTX A2000, NVIDIA RTX A3000, RTX A4000 and RTX A5000 laptop GPUs deliver accelerated performance without compromising mobility.

For the data center, there are the new NVIDIA A10 GPU and A16 GPU. The A10 provides up to 2.5x the virtual workstation performance of the previous generation for designers and engineers, while the A16 GPU provides up to 2x user density with lower total cost of ownership and an enhanced virtual desktop infrastructure experience over the previous generation.

NVIDIA today announced its first data center CPU, an Arm-based processor that will deliver 10x the performance of today's fastest servers on the most complex AI and high performance computing workloads.

The result of more than 10,000 engineering years of work, the NVIDIA Grace CPU is designed to address the computing requirements for the world's most advanced applications—including natural language processing, recommender systems and AI supercomputing—that analyze enormous datasets requiring both ultra-fast compute performance and massive memory. It combines energy-efficient Arm CPU cores with an innovative low-power memory subsystem to deliver high performance with great efficiency.