Supermicro, Inc. (NASDAQ: SMCI), a Total IT Solution Provider for AI, Cloud, Storage, and 5G/Edge, delivers an expanded portfolio of purpose-built infrastructure solutions to accelerate performance and increase efficiency in 5G and telecom workloads. With one of the industry's most diverse offerings, Supermicro enables customers to expand public and private 5G infrastructures with improved performance per watt and support for new and innovative AI applications. As a long-term advocate of open networking platforms and a member of the O-RAN Alliance, Supermicro's portfolio incorporates systems featuring 5th Gen Intel Xeon processors, AMD EPYC 8004 Series processors, and the NVIDIA Grace Hopper Superchip.

"Supermicro is expanding our broad portfolio of sustainable and state-of-the-art servers to address the demanding requirements of 5G and telco markets and Edge AI," said Charles Liang, president and CEO of Supermicro. "Our products are not just about technology, they are about delivering tangible customer benefits. We quickly bring data center AI capabilities to the network's edge using our Building Block architecture. Our products enable operators to offer new capabilities to their customers with improved performance and lower energy consumption. Our edge servers contain up to 2 TB of high-speed DDR5 memory, 6 PCIe slots, and a range of networking options. These systems are designed for increased power efficiency and performance-per-watt, enabling operators to create high-performance, customized solutions for their unique requirements. This reassures our customers that they are investing in reliable and efficient solutions."

NVIDIA is reported to be setting up an AI-focused semi-custom chip design business unit, according to inside sources known to Reuters—it is believed that Team Green leadership is adapting to demands leveraged by key data-center customers. Many companies are seeking cheaper alternatives, or have devised their own designs (budget/war chest permitting)—NVIDIA's current range of AI GPUs are simply off-the-shelf solutions. OpenAI has generated the most industry noise—their alleged early 2024 fund-raising pursuits have attracted plenty of speculative/kind-of-serious interest from notable semiconductor personalities.

Team Green is seemingly reacting to emerging market trends—Jensen Huang (CEO, president and co-founder) has hinted that NVIDIA custom chip designing services are on the cusp. Stephen Nellis—a Reuters reporter specializing in tech industry developments—has highlighted select NVIDIA boss quotes from an incoming interview piece: "We're always open to do that. Usually, the customization, after some discussion, could fall into system reconfigurations or recompositions of systems." The Team Green chief teased that his engineering team is prepared to take on the challenge meeting exact requests: "But if it's not possible to do that, we're more than happy to do a custom chip. And the benefit to the customer, as you can imagine, is really quite terrific. It allows them to extend our architecture with their know-how and their proprietary information." The rumored NVIDIA semi-custom chip design business unit could be introduced in an official capacity at next month's GTC 2024 Conference.

AI workloads are split into two different categories: training and inference. While training requires large computing and memory capacity, access speeds are not a significant contributor; inference is another story. With inference, the AI model must run extremely fast to serve the end-user with as many tokens (words) as possible, hence giving the user answers to their prompts faster. An AI chip startup, Groq, which was in stealth mode for a long time, has been making major moves in providing ultra-fast inference speeds using its Language Processing Unit (LPU) designed for large language models (LLMs) like GPT, Llama, and Mistral LLMs. The Groq LPU is a single-core unit based on the Tensor-Streaming Processor (TSP) architecture which achieves 750 TOPS at INT8 and 188 TeraFLOPS at FP16, with 320x320 fused dot product matrix multiplication, in addition to 5,120 Vector ALUs.

Having massive concurrency with 80 TB/s of bandwidth, the Groq LPU has 230 MB capacity of local SRAM. All of this is working together to provide Groq with a fantastic performance, making waves over the past few days on the internet. Serving the Mixtral 8x7B model at 480 tokens per second, the Groq LPU is providing one of the leading inference numbers in the industry. In models like Llama 2 70B with 4096 token context length, Groq can serve 300 tokens/s, while in smaller Llama 2 7B with 2048 tokens of context, Groq LPU can output 750 tokens/s. According to the LLMPerf Leaderboard, the Groq LPU is beating the GPU-based cloud providers at inferencing LLMs Llama in configurations of anywhere from 7 to 70 billion parameters. In token throughput (output) and time to first token (latency), Groq is leading the pack, achieving the highest throughput and second lowest latency.

Online hardware communities continue to discuss the 12VHPWR connection standard's troubled existence, while revised technology gets worked on—quietly—in the background. PCI-SIG's 12V-2x6 connector was first revealed last summer, signalling an alternative power delivery method for high-wattage graphics cards. Past TPU reports show that the 12V-2x6 16-pin design has already popped up on select NVIDIA Founders Edition cards, GeForce RTX 40 SUPER custom graphics card designs, and various new generation power supplies. Earlier today, Алексей (AKA wxnod) took to social media and posted an image of the freshly deshrouded "H++" 12V-2x6 (total design limit: 675 W) socket, as well as a shot of the familiar "H+" 12VHPWR (max. 600 W).

This fifth generation socket design largely rolled out with Team Green's GeForce RTX-40 SUPER card series, although wxnod notes that exceptions do exist: "Some AIC GeForce RTX 4070 SUPER, 4070 Ti SUPER and 4080 SUPER cards are still using the H+12VHPWR interface." The H++ identified 12V-2x6 design's power limit peaks at 675 W—a technical breakdown from last July revealed that 75 W comes from the expansion slot, while the big 600 W portion flows through the 16-pin connector. As mentioned before, 12V-2x6 debuted on a few Non-SUPER cards back in 2023, but last month's SUPER series product launch marked a more comprehensive rollout. AMD has indicated that it is considering an adoption of Gen 5 H++ in the future, but we have not heard much on that subject since last August. A new generation 16-pin PCIe 6.0 power connector design was linked to the upcoming NVIDIA RTX 50-series of "Blackwell" GPUs, but Hardware Busters has refuted rumors generated by Moore's Law is Dead. Team Green is expected to remain faithful to "H++" 12V-2x6 with the launch of next generation graphics cards.

NVIDIA today announced that Australia's Pawsey Supercomputing Research Centre will add the NVIDIA CUDA Quantum platform accelerated by NVIDIA Grace Hopper Superchips to its National Supercomputing and Quantum Computing Innovation Hub, furthering its work driving breakthroughs in quantum computing.

Researchers at the Perth-based center will leverage CUDA Quantum - an open-source hybrid quantum computing platform that features powerful simulation tools, and capabilities to program hybrid CPU, GPU and QPU systems - as well as, the NVIDIA cuQuantum software development kit of optimized libraries and tools for accelerating quantum computing workflows. The NVIDIA Grace Hopper Superchip - which combines the NVIDIA Grace CPU and Hopper GPU architectures - provides extreme performance to run high-fidelity and scalable quantum simulations on accelerators and seamlessly interface with future quantum hardware infrastructure.

EdgeCortix, the Japan-based fabless semiconductor company focused on energy-efficient AI processing, announced today that the Acquisitions, Technology and Logistics Agency (ATLA), Japan Ministry of Defense, will include the groundbreaking edge AI startup alongside an elite group of leading Japanese companies to represent Japan's air and defense innovation landscape at ATLA's booth at the Singapore Airshow to be held February 20 - 25. The Singapore Airshow is one of the largest and most influential shows of its kind in the world, and the largest in Asia, seeing as many as 50,000 attendees per biennial show. Over 1,000 companies from 50 countries are expected to participate in the 2024 show.

EdgeCortix's flagship product, the SAKURA-I chip, will be featured among a small handful of influential Japanese innovations at the booth. SAKURA-I is a dedicated co-processor that delivers high compute efficiency and low latency for artificial intelligence (AI) workloads that are carried out "at the edge", where the data is collected and mission critical decisions need to be made - far away from a datacenter. SAKURA-I delivers orders of magnitude better energy efficiency and processing speed than conventional semiconductors (ex: GPUs & CPUs), while drastically reducing operating costs for end users.

Providing a peek at the architecture powering advanced AI factories, NVIDIA released a video that offers the first public look at Eos, its latest data-center-scale supercomputer. An extremely large-scale NVIDIA DGX SuperPOD, Eos is where NVIDIA developers create their AI breakthroughs using accelerated computing infrastructure and fully optimized software. Eos is built with 576 NVIDIA DGX H100 systems, NVIDIA Quantum-2 InfiniBand networking and software, providing a total of 18.4 exaflops of FP8 AI performance. Revealed in November at the Supercomputing 2023 trade show, Eos—named for the Greek goddess said to open the gates of dawn each day—reflects NVIDIA's commitment to advancing AI technology.

Eos Supercomputer Fuels Innovation
Each DGX H100 system is equipped with eight NVIDIA H100 Tensor Core GPUs. Eos features a total of 4,608 H100 GPUs. As a result, Eos can handle the largest AI workloads to train large language models, recommender systems, quantum simulations and more. It's a showcase of what NVIDIA's technologies can do, when working at scale. Eos is arriving at the perfect time. People are changing the world with generative AI, from drug discovery to chatbots to autonomous machines and beyond. To achieve these breakthroughs, they need more than AI expertise and development skills. They need an AI factory—a purpose-built AI engine that's always available and can help ramp their capacity to build AI models at scale Eos delivers. Ranked No. 9 in the TOP 500 list of the world's fastest supercomputers, Eos pushes the boundaries of AI technology and infrastructure.

An Ebay Store—customgpu_official—is selling memory modified GeForce RTX 2080 Ti graphics cards. The outfit (located in Palo Alto, California) has a large inventory of MSI GeForce RTX 2080 Ti AERO cards—judging from their listing's photo gallery. Workers in China are reportedly upgrading these (possibly refurbished) units with extra lashings of GDDR6 VRAM—going from the original 11 GB specification up to 22 GB. We have observed smaller scale GeForce RTX 2080 Ti modification projects and a very ambitious user-modified example in the past, but customgpu's latest endeavor targets a growth industry—the item description states: "Why do you need a 22 GB 2080 Ti? Large VRAM is essential to cool AIGC apps such as stable diffusion fine tuning, LLAMA, LLM." At the time of writing three cards are available to purchase, and interested customers have already acquired four memory modded units.

They advertise their upgraded "Turbo Edition" card as a great "budget alternative" to more modern GeForce RTX 3090 and 4090 models—"more information and videos" can be accessed via 2080ti22g.com. The MSI GeForce RTX 2080 Ti AERO 11 GB model is not documented within TPU's GPU database, but its dual-slot custom cooling solution is also sported by the MSI RTX 2080 SUPER AERO 8 GB graphics card. The AERO's blower fan system creates a "mini-wind tunnel, pulling fresh air from inside the case and blowing it out the IO panel, and out of the system." The seller's asking price is $499 per unit—perhaps a little bit steep for used cards (potentially involved in mining activities), but customgpu_official seems to be well versed in repairs. Other Ebay listings show non-upgraded MSI GeForce RTX 2080 Ti AERO cards selling in the region of $300 to $400. Custom GPU Upgrade and Repair's hype video proposes that their modified card offers great value, given that it sells for a third of the cost of a GeForce RTX 3090—their Ebay item description contradicts this claim: "only half price compared with GeForce RTX 3090 with almost the same GPU memory."

The MSI Afterburner 4.6.6 Beta update was released three days ago—available to download through Guru3D's distribution section—its patch notes tease the exciting addition of "some future NVIDIA GPU PCI DeviceIDs to (our) hardware database." The forward facing nature of this software upgrade brings some unfortunate news for Windows XP operating system users—Beta version 4.6.6's top bullet point provides some reasoning: "Ported to VC++ 2022 compiler. Please take a note that due to this change MSI Afterburner will no longer be able to start under Windows XP. Please stay on the previous versions of the product if you need this OS support." Unwinder's software engineering team has traditionally stuck with the 2008 Visual C++ compiler, hence Afterburner's long history of supporting Windows XP.

The adoption of a more modern compiler has signaled the end for MSI's overclocking and hardware monitoring program on a legacy operating system. Developers largely moved on from XP-supporting endeavors around the mid-2010s—as pointed out by Tom's Hardware: "To get an idea on how late Afterburner is on dropping Windows XP, the last time we reported on any app ending support for the OS was in 2019, when Steam ended support on New Year's Day." Returning to the modern day—4.6.6 Beta's best-of-list mentions that RivaTuner Statistics Server is host to "more than 90 compatibility enhancements and changes"—v7.3.5 rolls out with NVIDIA Reflex and PresentMon integration, as well as programmable conditional layers support. The other headlining feature addition within Afterburner's latest pre-release guise is voltage control for AMD Radeon RX 7800 XT GPUs.

Building on our previously announced support of the AMD Radeon RX 7900 XT, XTX and Radeon PRO W7900 GPUs with AMD ROCm 5.7 and PyTorch, we are now expanding our client-based ML Development offering, both from the hardware and software side with AMD ROCm 6.0. Firstly, AI researchers and ML engineers can now also develop on Radeon PRO W7800 and on Radeon RX 7900 GRE GPUs. With support for such a broad product portfolio, AMD is helping the AI community to get access to desktop graphics cards at even more price points and at different performance levels.

Furthermore, we are complementing our solution stack with support for ONNX Runtime. ONNX, short for Open Neural Network Exchange, is an intermediary Machine Learning framework used to convert AI models between different ML frameworks. As a result, users can now perform inference on a wider range of source data on local AMD hardware. This also adds INT8 via MIGraphX—AMD's own graph inference engine—to the available data types (including FP32 and FP16). With AMD ROCm 6.0, we are continuing our support for the PyTorch framework bringing mixed precision with FP32/FP16 to Machine Learning training workflows.

Generative AI is driving change across industries—and to take advantage of its benefits, businesses must select the right hardware to power their workflows. The new NVIDIA RTX 2000 Ada Generation GPU delivers the latest AI, graphics and compute technology to compact workstations, offering up to 1.5x the performance of the previous-generation RTX A2000 12 GB in professional workflows. From crafting stunning 3D environments to streamlining complex design reviews to refining industrial designs, the card's capabilities pave the way for an AI-accelerated future, empowering professionals to achieve more without compromising on performance or capabilities. Modern multi-application workflows, such as AI-powered tools, multi-display setups and high-resolution content, put significant demands on GPU memory. With 16 GB of memory in the RTX 2000 Ada, professionals can tap the latest technologies and tools to work faster and better with their data.

Powered by NVIDIA RTX technology, the new GPU delivers impressive realism in graphics with NVIDIA DLSS, delivering ultra-high-quality, photorealistic ray-traced images more than 3x faster than before. In addition, the RTX 2000 Ada enables an immersive experience for enterprise virtual-reality workflows, such as for product design and engineering design reviews. With its blend of performance, versatility and AI capabilities, the RTX 2000 Ada helps professionals across industries achieve efficiencies. Architects and urban planners can use it to accelerate visualization workflows and structural analysis, enhancing design precision. Product designers and engineers using industrial PCs can iterate rapidly on product designs with fast, photorealistic rendering and AI-powered generative design. Content creators can edit high-resolution videos and images seamlessly, and use AI for realistic visual effects and content creation assistance. And in vital embedded applications and edge computing, the RTX 2000 Ada can power real-time data processing for medical devices, optimize manufacturing processes with predictive maintenance and enable AI-driven intelligence in retail environments.

AMD has quietly funded an effort over the past two years to enable binary compatibility for NVIDIA CUDA applications on their ROCm stack. This allows CUDA software to run on AMD Radeon GPUs without adapting the source code. The project responsible is ZLUDA, which was initially developed to provide CUDA support on Intel graphics. The developer behind ZLUDA, Andrzej Janik, was contracted by AMD in 2022 to adapt his project for use on Radeon GPUs with HIP/ROCm. He spent two years bringing functional CUDA support to AMD's platform, allowing many real-world CUDA workloads to run without modification. AMD decided not to productize this effort for unknown reasons but did open-source it once funding ended per their agreement. Over at Phoronix, there were several benchmarks testing AMD's ZLUDA implementation over a wide variety of benchmarks.

Benchmarks found that proprietary CUDA renderers and software worked on Radeon GPUs out-of-the-box with the drop-in ZLUDA library replacements. CUDA-optimized Blender 4.0 rendering now runs faster on AMD Radeon GPUs than the native ROCm/HIP port, reducing render times by around 10-20%, depending on the scene. The implementation is surprisingly robust, considering it was a single-developer project. However, there are some limitations—OptiX and PTX assembly codes still need to be fully supported. Overall, though, testing showed very promising results. Over the generic OpenCL runtimes in Geekbench, CUDA-optimized binaries produce up to 75% better results. With the ZLUDA libraries handling API translation, unmodified CUDA binaries can now run directly on top of ROCm and Radeon GPUs. Strangely, the ZLUDA port targets AMD ROCm 5.7, not the newest 6.x versions. Only time will tell if AMD continues investing in this approach to simplify porting of CUDA software. However, the open-sourced project now enables anyone to contribute and help improve compatibility. For a complete review, check out Phoronix tests.

NVIDIA's decision to shave off $200 from its GeForce RTX 4080 GPU tier has caused a run on retail since the launch of SUPER variants late last month—VideoCardz has investigated an apparent North American supply shortage. The adjusted $999 base MSRP appears to be an irresistible prospect for discerning US buyers—today's report explains how: "a week after its release, that GeForce RTX 4080 SUPER cards are not available at any major US retailer for online orders." At the time of writing, no $999 models are available to purchase via e-tailers (for delivery)—BestBuy and Micro Center have a smattering of baseline MSRP cards (including the Founders Edition), but for in-store pickup only. Across the pond, AD103 SUPER's supply status is a bit different: "On the other hand, in Europe, the situation appears to be more favorable, with several retailers listing the cards at or near the MSRP of €1109."

The cheapest custom GeForce RTX 4080 SUPER SKU, at $1123, seems to be listed by Amazon.com. Almost all of Newegg's product pages are displaying an "Out of Stock" notice—ZOTAC GAMING's GeForce RTX 4080 SUPER Trinity OC White Edition model is on "back order" for $1049.99, while the only "in stock" option is MSI's GeForce RTX 4080 Super Expert card (at $1149.99). VideoCardz notes that GeForce RTX 4070 SUPER and RTX 4070 TI SUPER models are in plentiful supply, which highlights a big contrast in market conditions for NVIDIA's latest Ada Lovelace families. The report also mentions an ongoing shortage of GeForce RTX 4080 (Non-SUPER) cards, going back weeks prior to the official January 31 rollout: "Similar to the RTX 4090, finding the RTX 4080 at its $1200 price point has proven challenging." Exact sales figures are not available to media outlets—it is unusual to see official metrics presented a week or two after a product's launch—so we will have to wait a little longer to find out whether demand has far outstripped supply in the USA.

A new forecast from International Data Corporation (IDC) shows shipments of artificial intelligence (AI) PCs - personal computers with specific system-on-a-chip (SoC) capabilities designed to run generative AI tasks locally - growing from nearly 50 million units in 2024 to more than 167 million in 2027. By the end of the forecast, IDC expects AI PCs will represent nearly 60% of all PC shipments worldwide.

"As we enter a new year, the hype around generative AI has reached a fever pitch, and the PC industry is running fast to capitalize on the expected benefits of bringing AI capabilities down from the cloud to the client," said Tom Mainelli, group vice president, Devices and Consumer Research. "Promises around enhanced user productivity via faster performance, plus lower inferencing costs, and the benefit of on-device privacy and security, have driven strong IT decision-maker interest in AI PCs. In 2024, we'll see AI PC shipments begin to ramp, and over the next few years, we expect the technology to move from niche to a majority."

CableMod issued a statement—just before the last Christmas holiday—detailing a safety recall of 16-pin 12VHPWR angled adapters, version 1.0 and 1.1. This announcement received widespread media coverage (at least in tech circles), but some unfortunate customers have not yet received the memo about faulty adapters—CableMod's 90° angled and 180° hard connectors can overheat and in worst case scenarios, actually melt. HotHardware, amusingly named given this context, was the first hardware news outlet to notice that the Consumer Product Safety Commission (CPSC) had published a "GPU Angled Adapter" recall notice to its website earlier today, under "Recall number 24-112."

The US government body's listing outlines aforementioned hazardous conditions, along with an estimated 25,300 affected unit count. The CPSC's recommended "Remedy" advice is as follows: "Consumers should immediately stop using the recalled angled adapters and contact CableMod for instructions on how to safely remove their adapter from the GPU and for a full refund, including cost of shipping, or a $60 store credit for non-customized products, with free standard shipping. Consumers will be asked to destroy the adapter and upload a photo of the destroyed product to cablemod.com/adapterrecall/. The instructions on how to safely remove the adapter are also located on that site. Once destroyed, consumers should discard the adapter in accordance with local laws." The Safety Commission has gathered some customer feedback intelligence on this matter: "The firm (CableMod Ltd., of China) has received 272 reports of the adapters becoming loose, overheating and melting into the GPU, with at least $74,500 in property damage claims in the United States. No injuries have been reported."

Phoronix head honcho, Michael Larabel, has noticed another set of interesting updates for AMD Graphics on Linux—albeit in preparation for next generation solutions: "engineers on Monday (February 5) posted a few new patch series for enabling some updated IP (intellectual property) blocks within their open-source AMDGPU Linux kernel graphics driver. This new IP is presumably part of the ongoing hardware enablement work for their next-gen RDNA 4 graphics." Team Red GitHub patches for "GFX12" targets appeared online last November, again highlighted by Larabel's investigative work—AMD engineers appear to be quite determined with their open-source software endeavors, as seen in LLVM-Project notes regarding GFX1200's enablement.

The new "IP block" updates included patches for the enabling ATHUB 4.1, LSDMA 7.0, IH 7.0, and HDP 7.0—presumably for next generation Radeon graphics solutions. Larabel provided a quick breakdown of these components: "ATHUB 4.1 is needed for clock-gating / power management features, LSDMA 7.0 is the latest IP for Light SDMA for general purpose System DMA (SDMA) on the GPU, IH 7.0 for the Interrupt Handler on the GPU, and HDP 7.0 for the Host Data Path support for CPU accessing the GPU device memory via the PCI BAR. As far as code changes, the big chunks of the work are from the auto-generated header files." He believes that AMD's engineers have largely moved on from current generation tasks: "The big version bumps for these IP blocks all the more are likely indicative of these bits being for next-gen RDNA 4 as opposed to further iterating on RDNA3 or similar." The patches could be merged into the upcoming Linux 6.9 release, possibly coinciding with a Radeon RX 8000 series rollout.

Huawei's Ascend 910B AI GPU is reportedly in high demand in China—we last learned that NVIDIA's latest US sanction-busting H20 "Hopper" model is lined up as a main competitor, allegedly in terms of both pricing and performance. A recent Reuters report proposes that Huawei is reacting to native enterprise market trends by shifting its production priorities—in favor of Ascend product ranges, while demoting their Kirin smartphone chipset family. Generative AI industry experts believe that the likes of Alibaba and Tencent have rejected Team Green's latest batch of re-jigged AI chips (H20, L20 and L2)—tastes have gradually shifted to locally developed alternatives.

Huawei leadership is seemingly keen to seize these growth opportunities—their Ascend 910B is supposedly ideal for workloads "that require low-to-mind inferencing power." Reuters has spoken to three anonymous sources—all with insider knowledge of goings-on at a single facility that manufacturers Ascend AI chips and the Kirin smartphone SoCs. Two of the leakers claim that this unnamed fabrication location is facing many "production quality" challenges, namely output being "hamstrung by a low yield rate." The report claims that Huawei has pivoted by deprioritizing Kirin 9000S (7 nm) production, thus creating a knock-on effect for its premium Mate 60 smartphone range.

PowerColor, a leader in innovative graphics card solutions, is proud to announce the launch of its latest marvel in the gaming world: the PowerColor RX 7900 XT Hellhound - Spectral White Edition. Following the overwhelming success of the 7800 XT Spectral White model, this new release brings the same unique design elements to the powerful Radeon 7900 XT series.

Spectral White Edition: A Symphony in White
The RX 7900 XT Hellhound Spectral White Edition is a testament to PowerColor's commitment to exceptional design and engineering. It features an all-white PCB, heatsink, and cooling solution, setting a new benchmark in graphics card aesthetics. This card is not just a performance powerhouse; it's a statement piece for any gaming setup, offering a pristine, unified look that white PC build enthusiasts will adore.

AMD's December 2023 launch of new Instinct series accelerators has generated a lot of tech news buzz and excitement within the financial world, but not many folks are privy to Team Red's MSRP for the CDNA 3.0 powered MI300X and MI300A models. A Citi report has pulled back the curtain, albeit with "projected" figures—an inside source claims that Microsoft has purchased the Instinct MI300X 192 GB model for ~$10,000 a piece. North American enterprise customers appear to have taken delivery of the latest MI300 products around mid-January time—inevitably, top secret information has leaked out to news investigators. SeekingAlpha's article (based on Citi's findings) alleges that the Microsoft data center division is AMD's top buyer of MI300X hardware—GPT-4 is reportedly up and running on these brand new accelerators.

The leakers claim that businesses further down the (AI and HPC) food chain are having to shell out $15,000 per MI300X unit, but this is a bargain when compared to NVIDIA's closest competing package—the venerable H100 SXM5 80 GB professional card. Team Green, similarly, does not reveal its enterprise pricing to the wider public—Tom's Hardware has kept tabs on H100 insider info and market leaks: "over the recent quarters, we have seen NVIDIA's H100 80 GB HBM2E add-in-card available for $30,000, $40,000, and even much more at eBay. Meanwhile, the more powerful H100 80 GB SXM with 80 GB of HBM3 memory tends to cost more than an H100 80 GB AIB." Citi's projection has Team Green charging up to four times more for its H100 product, when compared to Team Red MI300X pricing. NVIDIA's dominant AI GPU market position could be challenged by cheaper yet still very performant alternatives—additionally chip shortages have caused Jensen & Co. to step outside their comfort zone. Tom's Hardware reached out to AMD for comment on the Citi pricing claims—a company representative declined this invitation.

An Open Image Denoise 2.2 release candidate was released earlier today—as discovered by Phoronix's founder and principal writer; Michael Larabel. Intel's dedicated website has not been updated with any new documentation or changelogs (at the time of writing), but a GitHub release page shows all of the crucial information. Team Blue's open-source oneAPI has been kept up-to-date with the latest technologies—not only limited to Intel's stable of Xe-LP, Xe-HPG and Xe-HPC components—the Phonorix article highlights updated support on competing platforms. The v2.2 preview adds support for Meteor Lake's integrated Arc graphics solution, and additional "denoising quality enhancements and other improvements."

Non-Intel platform improvements include updates for Apple's M-series chipsets, AArch64 processors, and NVIDIA CUDA. OIDn 2.2-rc: "adds Metal device support for Apple Silicon GPUs on recent versions of macOS. OIDn has already been supporting ARM64/AArch64 for Apple Silicon CPUs while now Open Image Denoise has extended that AArch64 support to work on Windows and Linux too. There is better performance in general for Open Image Denoise on CPUs with this forthcoming release." The changelog also highlights a general improvement performance across processors, and a fix that resolves a crash incident: "when releasing a buffer after releasing the device."

Palit Microsystems Ltd., a leading graphics card manufacturer, proudly announces the NVIDIA GeForce RTX 3050 6 GB KalmX and StormX Series graphics cards. The GeForce RTX 3050 6 GB GPU is built with the powerful graphics performance of the NVIDIA Ampere architecture. It offers dedicated 2nd gen RT Cores and 3rd gen Tensor Cores, new streaming multiprocessors, and high-speed G6 memory to tackle the latest games.

GeForce RTX 3050 6 GB KalmX: Passive Cooling. Silent Gaming
Introducing the Palit GeForce RTX 3050 KalmX, where silence meets performance in perfect harmony. The KalmX series, renowned for its ingenious fan-less design, redefines your gaming experience. With its passive cooling system, this graphics card operates silently, making it ideal for both gaming and multimedia applications. Available on shelves today—2nd February 2024.

Aetina, a leading global Edge AI solution provider, announces the release of its new embedded MXM GPU series utilizing the NVIDIA Ada Lovelace architecture - MX2000A-VP, MX3500A-SP, and MX5000A-WP. Designed for real-time ray tracing and AI-based neural graphics, this series significantly enhances GPU performance, delivering outstanding gaming and creative, professional graphics, AI, and compute performance. It provides the ultimate AI processing and computing capabilities for applications in smart healthcare, autonomous machines, smart manufacturing, and commercial gaming.

The global GPU (graphics processing unit) market is expected to achieve a 34.4% compound annual growth rate from 2023 to 2028, with advancements in the artificial intelligence (AI) industry being a key driver of this growth. As the trend of AI applications expands from the cloud to edge devices, many businesses are seeking to maximize AI computing performance within minimal devices due to space constraints in deployment environments. Aetina's latest embedded MXM modules - MX2000A-VP, MX3500A-SP, and MX5000A-WP, adopting the NVIDIA Ada Lovelace architecture, not only make significant breakthroughs in performance and energy efficiency but also enhance the performance of ray tracing and AI-based neural graphics. The modules, with their compact design, efficiently save space, thereby opening up more possibilities for edge AI devices.

GIGABYTE TECHNOLOGY Co. Ltd, a leading manufacturer of premium gaming hardware, today launches the GeForce RTX 40 EAGLE OC ICE series graphics cards powered by NVIDIA ADA Lovelace architecture. The latest EAGLE OC ICE series presents a white iteration of the well-received EAGLE OC graphics card series. With exceptional performance catering to the diverse requirements of gamers, creators, and AI developers, it features an extensive integration of white materials in its design. This introduces an alternative choice for gamers who appreciate white-themed setups.

GIGABYTE has introduced four models in the GeForce RTX 40 EAGLE OC ICE series, corresponding to the GeForce RTX 4070 Ti SUPER, GeForce RTX 4070 SUPER, GeForce RTX 4060 Ti, and GeForce RTX 4060 GPUs. The EAGLE OC ICE series features a brand-new white exterior design inspired by space technology and incorporates futuristic design elements. The graphics cards come with white covers and backplates, complemented by cosmic-themed graphics, symbols, and geometric shapes, providing a unique and personalized appearance for white-themed desktop setups.

GIGABYTE TECHNOLOGY Co. Ltd, a leading manufacturer of premium gaming hardware, today announced new GeForce RTX 3050 6G graphics cards. The GeForce RTX 3050 EAGLE OC 6G and GeForce RTX 3050 OC Low Profile 6G graphics cards are powered by Ampere- NVIDIA's 2nd gen RTX architecture, featuring dedicated RT cores, AI Tensor cores, and fast GDDR6 graphics memory. They deliver the most realistic ray tracing graphics and advanced AI features with DLSS. In addition to providing gamers with a visually stunning and smooth 1080p gaming experience, creators can also indulge in the joy of creative expression.

The GIGABYTE GeForce RTX 3050 EAGLE OC 6G graphics card incorporates futuristic design elements, presenting distinctive and personalized features through cosmic-themed graphics, symbols, and geometric shapes. The GIGABYTE GeForce RTX 3050 EAGLE OC 6G is equipped with the GIGABYTE WINDFORCE cooling system. Featuring unique blade fans, alternate spinning, and fan stop functionalities, this cooling system efficiently lowers the working temperature of the graphics card, ensuring stable performance even under high-demand operations.

NVIDIA's H800 AI GPU was rolled out last year to appease the Sanction Gods—but later on, the US Government deemed the cutdown "Hopper" part to be far too potent for Team Green's Chinese enterprise customers. Last October, newly amended export conditions banned sales of the H800, as well as the slightly older (plus similarly gimped) A800 "Ampere" GPU in the region. NVIDIA's engineering team returned to the drawing board, and developed a new range of compliantly weakened products. An exclusive Reuters report suggests that Team Green is taking pre-orders for a refreshed "Hopper" GPU—the latest China-specific flagship is called "HGX H20." NVIDIA web presences have not been updated with this new model, as well as Ada Lovelace-based L20 PCIe and L2 PCIe GPUs. Huawei's competing Ascend 910B is said to be slightly more performant in "some areas"—when compared to the H20—according to insiders within the distribution network.

The leakers reckon that NVIDIA's mainland distributors will be selling H20 models within a price range of $12,000 - $15,000—Huawei's locally developed Ascend 910B is priced at 120,000 RMB (~$16,900). One Reuters source stated that: "some distributors have started advertising the (NVIDIA H20) chips with a significant markup to the lower end of that range at about 110,000 yuan ($15,320). The report suggests that NVIDIA refused to comment on this situation. Another insider claimed that: "distributors are offering H20 servers, which are pre-configured with eight of the AI chips, for 1.4 million yuan. By comparison, servers that used eight of the H800 chips were sold at around 2 million yuan when they were launched a year ago." Small batches of H20 products are expected to reach important clients within the first quarter of 2024, followed by a wider release in Q2. It is believed that mass production will begin around Spring time.