Two years and a half into its storied career, the NVIDIA GeForce RTX 3070 GPU has finally dropped below MSRP in one European territory. German customers will be stoked to jump on e-tailer CaseKing's new offer - ZOTAC's Gaming GeForce RTX 3070 Twin Edge LHR graphics card is currently available for 449 EUR (not counting additional fees), so a saving of 50 Euros from the recommended retail price (499 EUR/$499). 3DCenter seems to be the first hardware news outlet to report on an RTX 3070 GPU dropping under RRP. The RTX 3070 and 3060 Ti models have been best sellers for NVIDIA (and board partners) since late 2020, yet buyers have long complained about unreasonable asking prices, and semi-generous discounts have been very late in arriving - just in time for the succeeding model.

3DCenter has created an overview of the graphics card market in Germany and Austria, and its findings for May 2023 indicate a trend where: "GPU prices in Euros have consistently dropped by ~10% since the end of January, in single cases up to 20%." The overview places the RTX 3070 8 GB in a price bracket position between AMD's Radeon RX 6750XT 12 GB and RX 6800 16 GB (non-XT) SKUs, which brings recent marketing strategies to mind - Team Red thinks that their cards offer the buyer more VRAM for their money when cross examined with the competition.

As expected with AMD's activity on GitHub, ROCm 5.5 has now been officially released. It brings several big changes, including better RDNA 3 support. While officially focused on AMD's professional/workstation graphics cards, the ROCm 5.5 should also bring better support for Radeon RX 7000 series graphics cards on Linux.

Surprisingly, the release notes do not officially mention RDNA 3 improvements in its release notes, but those have been already tested and confirmed. The GPU support list is pretty short including AMD GFX9, RDNA, and CDNA GPUs, ranging from Radeon VII, Pro VII, W6800, V620, and Instinct lineup. The release notes do mention new HIP enhancements, enhanced stack size limit, raising it from 16k to 128k, new APIs, OpenMP enhancements, and more. You can check out the full release notes, downloads, and more details over at GitHub.

Customers from Japan to Ecuador and Sweden are using NVIDIA DGX H100 systems like AI factories to manufacture intelligence. They're creating services that offer AI-driven insights in finance, healthcare, law, IT and telecom—and working to transform their industries in the process. Among the dozens of use cases, one aims to predict how factory equipment will age, so tomorrow's plants can be more efficient.

Called Green Physics AI, it adds information like an object's CO2 footprint, age and energy consumption to SORDI.ai, which claims to be the largest synthetic dataset in manufacturing.

AMD's marketing department this week continued its battle to outwit arch rival NVIDIA in GPU VRAM pricing wars - Sasa Marinkovic, a senior director at Team Red's gaming promotion department, tweeted out a simple and concise statement yesterday: "Our @amdradeon 16 GB gaming experience starts at $499." He included a helpful chart that lines up part of the AMD Radeon GPU range against a couple of hand-picked NVIDIA GeForce RTX cards, with emphasis on comparing pricing and respective allotments of VRAM. The infographic indicates AMD's first official declaration of the (last generation "Big Navi" architecture) RX 6800 GPU bottoming out at $499, an all time low, as well as hefty cut affecting the old range topping RX 6950 XT - now available for $649 (an ASRock version is going for $599 at the moment). The RX 6800 XT sits in-between at $579, but it is curious that the RX 6900 XT did not get a slot on the chart.

AMD's latest play against NVIDIA in the video memory size stake is nothing really new - earlier this month it encouraged potential customers to select one of its pricey current generation RX 7900 XT or XTX GPUs. The main reason being that the hefty Radeon cards pack more onboard VRAM than equivalent GeForce RTX models - namely the 4070 Ti and 4080 - therefore future-proofed for increasingly memory hungry games. The latest batch of marketing did not account for board partner variants of the (RDNA3-based) RX 7900 XT GPU selling for as low as $762 this week.

NVIDIA's H100 has recently become available to use via Cloud Service Providers (CSPs), and it was only a matter of time before someone decided to benchmark its performance and compare it to the previous generation's A100 GPU. Today, thanks to the benchmarks of MosaicML, a startup company led by the ex-CEO of Nervana and GM of Artificial Intelligence (AI) at Intel, Naveen Rao, we have some comparison between these two GPUs with a fascinating insight about the cost factor. Firstly, MosaicML has taken Generative Pre-trained Transformer (GPT) models of various sizes and trained them using bfloat16 and FP8 Floating Point precision formats. All training occurred on CoreWeave cloud GPU instances.

Regarding performance, the NVIDIA H100 GPU achieved anywhere from 2.2x to 3.3x speedup. However, an interesting finding emerges when comparing the cost of running these GPUs in the cloud. CoreWeave prices the H100 SXM GPUs at $4.76/hr/GPU, while the A100 80 GB SXM gets $2.21/hr/GPU pricing. While the H100 is 2.2x more expensive, the performance makes it up, resulting in less time to train a model and a lower price for the training process. This inherently makes H100 more attractive for researchers and companies wanting to train Large Language Models (LLMs) and makes choosing the newer GPU more viable, despite the increased cost. Below, you can see tables of comparison between two GPUs in training time, speedup, and cost of training.

Intel has appointed Deepak Patil as the new corporate vice president and general manager of its Accelerated Computing Systems and Graphics (AXG) group. Patil is set to succeed Raja Koduri in this leadership role - company CEO Pat Gelsinger was the first person to announce news (last month) of Koduri's departure from Intel. At the time of his leaving Team Blue, Koduri's official job title was "Executive Vice President and Chief Architect" so the wording of his successor's executive ranking is slightly different. Patil is the current chief technology and strategy officer at the Intel Data Center and AI Group, and was previously senior vice president at Dell APEX USA. He will be taking over directly from interim AXG division leader Jeff McVeigh.

The official Intel statement regarding its new leadership appointment states: "Intel will deliver competitive accelerated computing products and build scalable systems with easy-to-program software on a predictable cadence. Deepak Patil will serve as the CVP and General Manager of the Accelerated Computing Systems and Graphics (AXG) group. Deepak recently held the position of DCAI Chief Technology and Strategy Officer. Having held senior engineering leadership positions across the high-tech industry, including being a founding member of Microsoft Azure and leading Dell's APEX as-a-service business, he understands the important role that software and open ecosystems play in enabling application developers and service providers to bring innovative solutions to market, at scale."

Naughty Dog and Iron Galaxy have released the new and big Title Update 1.0.4.0 for the PC version of The Last of Us Part 1, bringing CPU and GPU optimizations for the game, as well as fixing some previous bugs and crashes.

According to the release notes, the latest update optimizes CPU and GPU use throughout the game, as well as improves both texture and graphical fidelity and resolution on Low and Medium settings. There are several big fixes, including crashes that may occur when quitting to the main menu or during shader building, as well as the crash that may occur on AMD CPUs with affinity limited to X3D cores. There is also a fix for an issue where textures are rendered on AMD GPUs.

Sparkle, a Taiwanese computer electronics maker, is again entering the GPU market after almost ten years of inactivity in the space. A while back, Sparkle was one of NVIDIA's original Add-In Board (AIB) partners and helped them launch the GeForce 7900 PCI GPU. The company continued to make NVIDIA-based GPUs until GTX 700 series in 2013. After a decade, Sparkle is back again with ambitions to be Intel's AIB partner and announced not one but three graphics cards to start. Called A750 Titan, A750 Orc, and A380 Elf, these cards feature triple-fan, dual-fan, and single-fan coolers, respectively.

The first in line is the Sparkle A750 Titan, a triple-fan, 2.5-slot design based on Intel Arc A750 GPU. Featuring 8 GB of GDDR6 VRAM, this top-end A750 SKU is clocked at 2300 MHz, up from the factory's 2050 MHz frequency. Titan's smaller brother is Sparkle A750 Orc, a dual-fan, "2.2"-slot (we assume smaller than two and a half and bigger than two slots) GPU with the same A750 GPU; however, it clocked slightly lower at 2200 MHz. Both models feature single HDMI 2.0 and 3x DisplayPort 2.0 output ports and require two 8-pin PCI power connectors. Lastly, we have the Sparkle A380 Elf, a half-length, ITX-sized GPU that fits in two slots and has a single-fan cooler. It is based on Intel Arc A380 and has identical specifications without factory overclocks applied. Pricing and availability are currently unknown.

ChatGPT has surged in popularity over a few months, and usage of this software has been regarded as one of the fastest-growing apps ever. Based on a Large Language Model (LLM) called GPT-3.5/4, ChatGPT uses user input to form answers based on its extensive database used in the training process. Having billions of parameters, the GPT models used for GPT can give precise answers; however, sometimes, these models hallucinate. Given a question about a non-existing topic/subject, ChatGPT can induce hallucination and make up the information. To prevent these hallucinations, NVIDIA, the maker of GPUs used for training and inferencing LLMs, has released a software library to put AI in place, called NeMo Guardrails.

As the NVIDIA repository states: "NeMo Guardrails is an open-source toolkit for easily adding programmable guardrails to LLM-based conversational systems. Guardrails (or "rails" for short) are specific ways of controlling the output of a large language model, such as not talking about politics, responding in a particular way to specific user requests, following a predefined dialog path, using a particular language style, extracting structured data, and more." These guardrails are easily programmable and can stop LLMs from outputting unwanted content. For a company that invests heavily in the hardware and software landscape, this launch is a logical decision to keep the lead in setting the infrastructure for future LLM-based applications.

NVIDIA's rumored RTX 5000 Ada Generation GPU has been outed once again, according to VideoCardz - the cited source being a keen-eyed member posting information dumps on a laptop discussion forum. Team Green has released new driver documentation that makes mention of hardware ID "26B2" under an entry for a now supported device: "NVIDIA RTX 5000 Ada Generation." Forum admin StefanG3D posted the small discovery on their favored forum in the small hours of Sunday morning (April 23).

As reported last month, the NVIDIA RTX 5000 Ada is destined to sit between existing sibling workstation GPUs - the AD102-based RTX 6000 and AD104-based RTX 4000 SFF. Hardware tipster kopite7kimi has learned enough to theorize that the NVIDIA RTX 5000 Ada Generation workstation graphics card will feature 15,360 CUDA cores and 32 GB of GDDR6 memory. The AD102 GPU is expected to sit at the heart of this unannounced card.

CD Projekt RED, the developer of Cyberpunk 2077, has advertised including various super sampling technologies like NVIDIA DLSS, AMD FSR, and now Intel XeSS supersampling. With the inclusion of XeSS version 1.1, Intel's Arc Alchemist graphics cards can record a significant performance uplift. Thanks to the Intel game blog, we compare XeSS enabled versus XeSS disabled, measuring the ability to play Cyberpunk 2077 at 1080p Ultra settings with medium ray tracing enabled. The FPS comparison was conducted with Intel Arc A750 Limited Edition GPU, which was paired with Intel Core i9-13900K and 32 GB of RAM.

With XeSS off, the A750 GPU struggled and only reached 39 FPS. However, with XeSS set to performance, the number jumped to 67 FPS, making for a smooth user experience and gameplay. This is a 71% performance uplift, enabled by a new update in the game. Interestingly, Intel XeSS is computed on Arc's XMX Units, while NVIDIA and AMD compute their super sampling on shader units.

NVIDIA has begun selling its compact RTX 4000 Ada Lovelace graphics card, offering GeForce RTX 3070-like performance at a mere 70 W power consumption, allowing it to fit in almost all desktop PCs. The low-profile, dual-slot board is priced higher than the RTX 4080 as it targets professional users, but it can still be used in a regular gaming computer. PNY's RTX 4000 Ada generation graphics card is the first to reach consumer shelves, currently available for $1,444 at ShopBLT, a retailer known for obtaining hardware before its competitors. The card comes with four Mini-DisplayPort connectors, so an additional mDP-DP or mDP-HDMI adapter must be factored into the cost.

The NVIDIA RTX 4000 SFF Ada generation board features an AD104 GPU with 6,144 CUDA cores, 20 GB of GDDR6 ECC memory, and a 160-bit interface. With a fixed boost frequency floating around 1560 MHz to reduce overall board power consumption, the GPU is rated for just 70 Watts of power. To emphasize the efficiency, this card requires no external PCIe power connector, as all the juice is fed through the PCIe slot. The GA104 graphics processor in this configuration delivers a peak FP32 performance of 19.2 TFLOPS, comparable to the GeForce RTX 3070. The 20 GB of memory makes the card more valuable for professionals and AI researchers needing compact solutions. Although the card's performance is overshadowed by the recently launched GeForce RTX 4070, the RTX 4000 SFF Ada's professional drivers, support for professional software ISVs, and additional features make it a strong contender in the semi-professional market. Availability and pricing are expected to improve in the coming weeks as the card becomes more widely accessible.More images, along with specification table, follow.

Acer today announced new TravelMate business laptops, all powered by 13th Gen Intel Core vPro processors, and feature 16:10 premium OLED displays, 65 Wh fast charging long battery life, and secured log-in with fingerprint reader or IR camera, coming together to achieve the performance and mobility requirements of today's hybrid workforce.

Acer TravelMate P6 14
The latest TravelMate P6 14 is the ultimate premium business laptop for mobile professionals and executives. Professionals can experience elevated viewing experiences on a large screen surface with a 2.8K OLED (2880x1800) display panel, a 16:10 aspect ratio, and support for 100% coverage of the DCI-P3 color space. Powered by Intel vPro, and an Intel Evo design, the high-end business laptop is packed with power as it comes with 13th Gen Intel Core i7 processors, 32 GB LPDDR5 memory and a 65 Wh[1] fast-charging battery. Online business meetings and video calls are further enhanced with the laptop's FHD IR webcam, AI-powered noise-reduction technology through Acer PurifiedVoice, and upward-facing speakers with DTS Audio. A PrivacyPanel feature helps obscure viewing angles beyond 90° to defend against prying eyes. The TravelMate P6 14 laptop also features 2x2 Wi-Fi 6E and 5G connectivity for faster and stronger wireless internet connection needed by mobile professionals.

Giga Computing, a subsidiary of GIGABYTE and an industry leader in high-performance servers, server motherboards, and workstations, today announced a lineup of powerful GPU-centric servers with the latest AMD and Intel CPUs, including NVIDIA HGX H100 servers with both 4-GPU and 8-GPU modules. With growing interest in HPC and AI applications, specifically generative AI (GAI), this breed of server relies heavily on GPU resources to tackle compute-heavy workloads that handle large amounts of data. With the advent of OpenAI's ChatGPT and other AI chatbots, large GPU clusters are being deployed with system-level optimization to train large language models (LLMs). These LLMs can be processed by GIGABYTE's new design-optimized systems that offer a high level of customization based on users' workloads and requirements.

The GIGABYTE G-series servers are built first and foremost to support dense GPU compute and the latest PCIe technology. Starting with the 2U servers, the new G293 servers can support up to 8 dual-slot GPUs or 16 single-slot GPUs, depending on the server model. For the ultimate in CPU and GPU performance, the 4U G493 servers offer plenty of networking options and storage configurations to go alongside support for eight (Gen 5 x16) GPUs. And for the highest level of GPU compute for HPC and AI, the G393 & G593 series support NVIDIA H100 Tensor Core GPUs. All these new two CPU socket servers are designed for either 4th Gen AMD EPYC processors or 4th Gen Intel Xeon Scalable processors.

According to The Information, Microsoft has been working on creating custom processors for processing AI with a project codenamed Athena. Based on TSMC's 5 nm process, these chips are designed to accelerate AI workloads and scale to hundreds or even thousands of chips. With the boom of Large Language Models (LLMs) that require billions of parameters, training them requires a rapid increase of computational power to a point where companies purchase hundreds of thousands of GPUs from the likes of NVIDIA. However, creating custom processors is a familiar feat for a company like Microsoft. Hyperscalers like AWS, Google, and Meta are already invested in the creation of processors for AI training, and Microsoft is just joining as well.

While we don't have much information about these processors, we know that Microsoft started the project in 2019, and today these processors are in the hands of select employees of Microsoft and OpenAI that work with AI projects and need computational horsepower. Interestingly, some projections assume that if Microsoft could match NVIDIA's GPU performance, the cost would only be a third of NVIDIA's offerings. However, it is challenging to predict that until more information is provided. Microsoft plans to make these chips more widely available as early as next year; however, there is no specific information on when and how, but Azure cloud customers would be the most logical place to start.

A strong growth in AI server shipments has driven demand for high bandwidth memory (HBM). TrendForce reports that the top three HBM suppliers in 2022 were SK hynix, Samsung, and Micron, with 50%, 40%, and 10% market share, respectively. Furthermore, the specifications of high-end AI GPUs designed for deep learning have led to HBM product iteration. To prepare for the launch of NVIDIA H100 and AMD MI300 in 2H23, all three major suppliers are planning for the mass production of HBM3 products. At present, SK hynix is the only supplier that mass produces HBM3 products, and as a result, is projected to increase its market share to 53% as more customers adopt HBM3. Samsung and Micron are expected to start mass production sometime towards the end of this year or early 2024, with HBM market shares of 38% and 9%, respectively.

AI server shipment volume expected to increase by 15.4% in 2023
NVIDIA's DM/ML AI servers are equipped with an average of four or eight high-end graphics cards and two mainstream x86 server CPUs. These servers are primarily used by top US cloud services providers such as Google, AWS, Meta, and Microsoft. TrendForce analysis indicates that the shipment volume of servers with high-end GPGPUs is expected to increase by around 9% in 2022, with approximately 80% of these shipments concentrated in eight major cloud service providers in China and the US. Looking ahead to 2023, Microsoft, Meta, Baidu, and ByteDance will launch generative AI products and services, further boosting AI server shipments. It is estimated that the shipment volume of AI servers will increase by 15.4% this year, and a 12.2% CAGR for AI server shipments is projected from 2023 to 2027.

Resident TechPowerUp hardware database overseer T4C Fantasy has divulged some early information about a custom version of the NVIDIA GeForce RTX 4060 Ti GPU card - Colorful's catchily named iGame RTX 4060 Ti Ultra White OC model has been added to the TPU GPU database, and T4C Fantasy has revealed a couple of tidbits on Twitter. The GPU has been tuned to have a maximum boost clock of 2580 MHz, jumping from a base clock of 2310 MHz. According to past leaks the reference version of the GeForce RTX 4060 Ti has a default boost clock of 2535 MHz, so Colorful's engineers have managed to add another 45 MHz on top of that with their custom iteration - so roughly 2% more than the reference default.

T4C Fantasy also confirmed that the Colorful iGame RTX 4060 Ti Ultra W OC will be appointed with 8 GB of VRAM, which also matches the reference model's rumored memory spec. T4C Fantasy points out that brands have the option to produce RTX 4060 Ti cards with a larger pool of attached video memory, but launch models will likely stick with the standard allotment of 8 GB of VRAM. The RTX 4060 Ti is listed as being based on the Ada Lovelace GPU architecture (GPU variant AD106-350-A1), and T4C Fantasy expects that Team Green will stick with a 5 nm process size - contrary to reports of a transition to manufacturing on 4 nm (chez TSMC foundries).

AMD has published an exciting development for its Radeon Open Compute Ecosystem (ROCm) users today. Now, ROCm is coming to the Windows operating system, and the company has extended ROCm support for consumer graphics cards instead of only supporting professional-grade GPUs. This development milestone is essential for making AMD's GPU family more competent with NVIDIA and its CUDA-accelerated GPUs. For those unaware, AMD ROCm is a software stack designed for GPU programming. Similarly to NVIDIA's CUDA, ROCm is designed for AMD GPUs and was historically limited to Linux-based OSes and GFX9, CDNA, and professional-grade RDNA GPUs.

However, according to documents obtained by Tom's Hardware (which are behind a login wall), AMD has brought support for ROCm to Radeon RX 6900 XT, Radeon RX 6600, and R9 Fury GPU. What is interesting is not the inclusion of RX 6900 XT and RX 6600 but the support for R9 Fury, an eight-year-old graphics card. Also, what is interesting is that out of these three GPUs, only R9 Fury has full ROCm support, the RX 6900 XT has HIP SDK support, and RX 6600 has only HIP runtime support. And to make matters even more complicated, the consumer-grade R9 Fury GPU has full ROCm support only on Linux and not Windows. The reason for this strange selection of support has yet to be discovered. However, it is a step in the right direction, as AMD has yet to enable more functionality on Windows and more consumer GPUs to compete with NVIDIA.

An online tipster, posting on the Chinese blog site Weibo, has let slip that Qualcomm's upcoming Snapdragon 8 Gen 3 mobile chipset is touted to pack some hefty graphical capabilities. The suggested Adreno "750" smartphone and tablet GPU is touted to offer a 50% increase over the present generation Adreno 740 - as featured on the recently released and cutting-edge Snapdragon 8 Gen 2 chipset. The current generation top-of-the-range Snapdragon is no slouch when it comes to graphics benchmarks, where it outperforms Apple's prime contender - the Bionic A16 SoC.

The Snapdragon 8 Gen 3 SoC is expected to launch in the last quarter of 2023, but details of the flagship devices that it will power are non-existent at the time of writing. The tipster suggests that Qualcomm has decided to remain on TSMC's 4 nm process for its next generation mobile chipset - perhaps an all too safe decision when you consider that Apple has upped the stakes with the approach of its Bionic A17 SoC. It has been reported that the Cupertino, California-based company has chosen to fabricate via TSMC's 3 nm process, although the Taiwanese foundry is said to be struggling with its N3 production line. The engineers at Qualcomm's San Diego headquarters are alleged to be experimenting with increased clock speeds running on the next gen Adreno GPU - as high as 1.0 GHz - in order to eke out as much performance as possible, in anticipation of besting the Bionic A17 in graphics benchmarks. The tipster theorizes that Qualcomm will still have a hard time matching Apple in terms of pure CPU throughput, so the consolation prize will lie with a superior GPU getting rigged onto the Snapdragon 8 Gen 3.

Alphacool expands the portfolio of the Enterprise Solutions series for GPU water coolers and presents the new ES NV A100 80 GB PCIe, ES RTX A4000 with backplate and ES RTX 6000 Ada 48 GB.

To best dissipate the enormous waste heat of this GPU generation, the cooler is positioned close to the components to be cooled in an exemplary manner. The fin structure has been adapted and allows a very good water flow while increasing the cooling surface. The modified jetplate with improved inflow engine ensures optimal distribution of water on the cooling fins. The fully chromed copper base is resistant to acids, scratches and damages. The matte carbon finish gives the cooler a noble appearance. At the same time, this makes it interesting for private users who want to do without aRGB lighting.

AMD unveils the most powerful AMD Radeon Pro graphics cards, Offering unique features and leadership performance to tackle heavy to Extreme Professional Workloads - AMD today announced the AMD Radeon PRO W7000 Series graphics, its most-powerful workstation graphics cards to date. The AMD Radeon PRO W7900 and AMD Radeon PRO W7800 graphics cards are built on groundbreaking AMD RDNA 3 architecture, delivering significantly higher performance than the previous generation and exceptional performance-per-dollar compared to the competitive offering. The new graphics cards are designed for professionals to create and work with high-polygon count models seamlessly, deliver incredible image fidelity and color accuracy, and run graphics and compute-based applications concurrently without disruption to workflows.

AMD Radeon PRO W7000 Series graphics cards feature the world's first workstation GPU architecture based on AMD's advanced chiplet design, providing real-world multi-tasking performance and incredible power efficiency. The new graphics cards are also the first professional workstation GPUs to offer the new AMD Radiance Display Engine featuring DisplayPort 2.1 that delivers a superior visual experience, higher resolutions and more available colors than ever before.

According to Business Insider, Twitter has made a substantial investment into hardware upgrades at its North American datacenter operation. The company has purchased somewhere in the region of 10,000 GPUs - destined for the social media giant's two remaining datacenter locations. Insider sources claim that Elon Musk has committed to a large language model (LLM) project, in an effort to rival OpenAI's ChatGPT system. The GPUs will not provide much computational value in the current/normal day-to-day tasks at Twitter - the source reckons that the extra processing power will be utilized for deep learning purposes.

Twitter has not revealed any concrete plans for its relatively new in-house artificial intelligence project but something was afoot when, earlier this year, Musk recruited several research personnel from Alphabet's DeepMind division. It was theorized that he was incubating a resident AI research lab at the time, following personal criticisms levelled at his former colleagues at OpenAI, ergo their very popular and much adopted chatbot.

Intel has decided to re-organize its Max series of Data Center GPUs (codenamed Ponte Vecchio), as revealed to Tom's Hardware this week, with a particular model - the Data Center Max GPU 1350 set for removal from the lineup. Industry experts are puzzled by this decision, given that the 1350 has been officially "available" on the market since January 2023, following soon after the announcement of the entire Max range in November 2022. Intel has removed listings and entries for the Data Center GPU Max 1350 from its various web presences.

A (sort of) successor is in the works, Intel has lined up the Data Center Max GPU 1450 for release later in the year. This model will have a trimmed I/O bandwidth - this modification is likely targeting companies in China, where performance standards are capped at a certain level (via U.S. sanctions on GPU exports). An Intel spokesperson provided further details and reasons for rearranging the Max product range: "We launched the Intel Data Center Max GPU 1550 (600 W), which was initially targeted for liquid-cooled solutions only. We have since expanded our support by offering Intel Data Center Max GPU 1550 (600 W) to include air-cooled solutions."

Steam's latest March survey has put NVIDIA's GeForce RTX 3060 at the top, reaching over 10 percent and surpassing both the GTX 1060 and the RTX 2060. NVIDIA has been holding the crown with over 80 percent of users running on their GPUs, while AMD held just over 10 percent. This means that the NVIDIA RTX 3060 almost has more users on Steam than all AMD Radeon graphics cards combined. Intel holds just over 6 percent. Bear in mind that Intel and AMD numbers also include integrated GPUs.

When it comes to CPUs, there are 74.46 percent running on Intel CPUs and 25.54 percent on AMD. Most users use a 6-core CPU, 45.76, with 8-core CPUs taking 18.45 percent. The memory amount has obviously risen, as 56.92 percent run on 16 GB, and 22.41 percent have 32 GB systems. When it comes to OS, most users are running on Windows 10, 73.95 percent, while Windows 11 OS takes 22.41 percent. While some might argue that the Steam Survey is not exactly precise as it is apparently based on a random survey, it does give a general idea and shows the big picture.

On Wednesday, the MLCommons team released the MLPerf 3.0 Inference numbers, and there was an exciting submission from NVIDIA. Reportedly, NVIDIA has used software optimization to improve the already staggering performance of its latest H100 GPU by up to 54%. For reference, NVIDIA's H100 GPU first appeared on MLPerf 2.1 back in September of 2022. In just six months, NVIDIA engineers worked on AI optimizations for the MLPerf 3.0 release to find that basic software optimization can catalyze performance increases anywhere from 7-54%. The workloads for measuring the inferencing speed suite included RNN-T speech recognition, 3D U-Net medical imaging, RetinaNet object detection, ResNet-50 object classification, DLRM recommendation, and BERT 99/99.9% natural language processing.

What is interesting is that NVIDIA's submission is a bit modified. There are open and closed categories that vendors have to compete in, where closed is the mathematical equivalent of a neural network. In contrast, the open category is flexible and allows vendors to submit results based on optimizations for their hardware. The closed submission aims to provide an "apples-to-apples" hardware comparison. Given that NVIDIA opted to use the closed category, performance optimization of other vendors such as Intel and Qualcomm are not accounted for here. Still, it is interesting that optimization can lead to a performance increase of up to 54% in NVIDIA's case with its H100 GPU. Another interesting takeaway is that some comparable hardware, like Qualcomm Cloud AI 100, Intel Xeon Platinum 8480+, and NeuChips's ReccAccel N3000, failed to finish all the workloads. This is shown as "X" on the slides made by NVIDIA, stressing the need for proper ML system software support, which is NVIDIA's strength and an extensive marketing claim.