TrendForce underscores that the primary momentum for server shipments this year remains with American CSPs. However, due to persistently high inflation and elevated corporate financing costs curtailing capital expenditures, overall demand has not yet returned to pre-pandemic growth levels. Global server shipments are estimated to reach approximately. 13.654 million units in 2024, an increase of about 2.05% YoY. Meanwhile, the market continues to focus on the deployment of AI servers, with their shipment share estimated at around 12.1%.

Foxconn is expected to see the highest growth rate, with an estimated annual increase of about 5-7%. This growth includes significant orders such as Dell's 16G platform, AWS Graviton 3 and 4, Google Genoa, and Microsoft Gen9. In terms of AI server orders, Foxconn has made notable inroads with Oracle and has also secured some AWS ASIC orders.

Intel CEO Pat Gelsinger considers NVIDIA "extraordinarily lucky" to be leading the AI hardware industry. In a recent public discussion with the students of MIT's engineering school to discuss the state of the semiconductor industry, Gelsinger said that Intel should be the one to be leading AI, but instead NVIDIA got lucky. We respectfully disagree. What Gelsinger glosses over with this train of thought is how NVIDIA got here. What NVIDIA has in 2023 is the distinction of being one of the hottest tech stocks behind Apple, the highest market share in a crucial hardware resource driving the AI revolution, and of course the little things, like market leadership over the gaming GPU market. What it doesn't have, is access to the x86 processor IP.

NVIDIA has, for long, aspired to be a CPU company, right from its rumored attempt to merge with AMD in the early/mid 2000s, to its stint with smartphone application processors with Tegra, an assortment of Arm-based products along the way, and most recently, its spectacularly unsuccessful attempt to acquire Arm from Softbank. Despite limited luck with the CPU industry, to level up to Intel, AMD, or even Qualcomm and MediaTek; NVIDIA never lost sight of its goal to be a compute hardware superpower, which is why, in our opinion, it owns the AI hardware market. NVIDIA isn't lucky, it spent 16 years getting here.

Tesla first revealed plans for its Dojo D1 training chip back in 2021, with hopes of it powering self-driving technology in the near future. The automative division has relied mostly on NVIDIA over the ensuing years, but is seemingly keen to move onto proprietary solutions. Media reports from two years ago suggest that 5760 NVIDIA A100 GPUs were in play to develop Tesla's advanced driver-assistance system (Autopilot ADAS). Tom's Hardware believed that a $300 Million AI supercomputer cluster—comprised of roughly 10,000 NVIDIA H100 GPUs—was powered on last month. Recent reports emerging from Taiwan suggest that Tesla is doubling Dojo D1 supercomputer chip orders with TSMC.

An Economic Daily report posits that 10,000 Dojo D1 are in a production queue for the next year, with insiders believing that Tesla is quietly expressing confidence in its custom application-specific integrated circuit (ASIC). An upcoming order count could increase for the next batch (in 2025). The article hints that TSMC's "HPC-related order momentum has increased thanks to Tesla." Both organizations have not publicly commented on these developments, but insider sources have disclosed some technical details—most notably that the finalized Dojo design: "mainly uses TSMC's 7 nm family process and combines it with InFO-level system-on-wafer (SoW) advanced packaging."

It's an exciting time in AI for business. As we apply the technology more widely across areas ranging from customer service to HR to code modernization, artificial intelligence (AI) is helping increasing numbers of us work smarter, not harder. And as we are just at the start of the AI for business revolution, the potential for improving productivity and creativity is vast. But AI today is an incredibly dynamic field, and AI platforms must reflect that dynamism, incorporating the latest advances to meet the demands of today and tomorrow. This is why we at IBM continue to add powerful new capabilities to IBM watsonx, our data and AI platform for business.

We have announced our latest addition: a new family of IBM-built foundation models which will be available in watsonx.ai, our studio for generative AI, foundation models and machine learning. Collectively named "Granite," these multi-size foundation models apply generative AI to both language and code. And just as granite is a strong, multipurpose material with many uses in construction and manufacturing, so we at IBM believe these Granite models will deliver enduring value to your business. But now let's take a look under the hood and explain a little about how we built them, and how they will help you take AI to the next level in your business.

According to the job listing found by Electrek, Tesla is currently hiring staff for Tesla's "1st of its kind Data Centers." Tesla is a company with a huge demand for computing, especially with training self-driving technology on its hardware. The company is building its training chips called Dojo D1, which is used to train neural networks that power the company's Full Self Driving (FSD) that is inferenced locally on each Tesla vehicle. However, to support such training infrastructure and other data processing, the company is in need of its own data centers, and the recruitment for it has just started.

It is interesting to mention a "first of its kind" data center, meaning that some unique design and/or application goal will be present. The global data center is roughly a 250 billion USD market, and with Tesla entering, we are still waiting to see the size of its investment. Nonetheless, the latest position, "Engineering Program Manager, Data Centers," will oversee these efforts and lead the end-to-end design and engineering of this supposedly unique data center.

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

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

Elon Musk in a late-Thursday tweet announced that he is placing his Twitter acquisition bid on "temporary hold" over doubts about the platform's spam-bot data. Twitter, in a recent SEC regulatory filing, disclosed that spam bots made up less than 5% of its userbase. The filing revealed that Twitter has 229 million users that viewed consistent ads, while fewer than 5% of the "monetizable daily active users" were fake or spam-bot accounts. Financial analysts predict the substantial fall in cryprocurrency values, as well as a $400 billion drop in market-capitalization of the Tesla stock since Musk announced plans to buy Twitter, may have made the world's richest man squeamish about buying Twitter, and that he is probably looking for a legally safe escape route from the deal. Twitter shares plummeted in value since the Musk tweet.

One of the electric vehicle driving forces in the car market, Tesla, has today announced that the company would have to issue a soft recall of a few select car models over an issue with overheating. The affected vehicles are Tesla Model 3 2022, Tesla Model S 2021-2022, Tesla Model X 2021-2022, and Tesla Model Y 2022. Tesla's infotainment system is powered by AMD Ryzen APUs, replacing the Intel Atom CPUs found in the previous models. With Ryzen APUs overheating, the infotainment system can lag or restart and sometimes cause it to get completely turned off. The problem is that the car's liquid cooling will prioritize cooling the batteries instead of the processor, causing it to overheat. Tesla issued a soft recall on these models, meaning that a regular firmware update will fix this issue.

TeslaTesla, Inc. (Tesla) is recalling certain 2021-2022 Model S, Model X, and 2022 Model 3 and Model Y vehicles operating certain firmware releases. The infotainment central processing unit (CPU) may overheat during the preparation or process of fast-charging, causing the CPU to lag or restart. A lagging or restarting CPU may prevent the center screen from displaying the rearview camera image, gear selection, windshield visibility control settings, and warning lights, increasing the risk of a crash. Tesla will perform an over-the-air (OTA) software update that will improve CPU temperature management, free of charge. Owner notification letters are expected to be mailed July 1, 2022. Owners may contact Tesla customer service at 1-877-798-3752. Tesla's number for this recall is SB-22-00-009.

Tesla CEO Elon Musk has recently stated that Tesla is currently working on adding support for Steam games to the Linux-powered infotainment system found in Tesla cars. The latest hardware version of the Tesla infotainment system features a quad-core AMD Zen+ CPU paired with an Radeon Navi 23 GPU similar to that of the Xbox Series X/S, PlayStation 5, and Steam Deck. The GPU includes 28 Compute Units running at 2.8 GHz to drive the 17-inch 2200x1300 center screen for approximately 10 TFLOPS of performance. Tesla has previously worked to bring individual games to the infotainment system such as Beach Buggy Racing 2, The Battle of Polytopia, Cuphead, Stardew Valley, and Fallout Shelter in addition to the Atari 2600 emulator. The timeline for any such implementation is likely to be in the medium to long term.

Elon MuskWe're working through the general case of making Steam games work on a Tesla vs specific titles. Former is obviously where we should be long-term.

In 2016, NVIDIA announced that the company is working on replacing its Fast Logic Controller processor codenamed Falcon with a new GPU System Processor (GSP) solution based on RISC-V Instruction Set Architecture (ISA). This novel RISC-V processor is codenamed NV-RISCV and has been used as GPU's controller core, coordinating everything in the massive pool of GPU cores. Today, NVIDIA has decided to open this NV-RISCV CPU to a broader spectrum of applications starting with 510.39 drivers. According to the NVIDIA documents, this is only available in the select GPUs for now, mainly data-centric Tesla accelerators.

NVIDIA DocumentsSome GPUs include a GPU System Processor (GSP) which can be used to offload GPU initialization and management tasks. This processor is driven by the firmware file /lib/firmware/nvidia/510.39.01/gsp.bin. A few select products currently use GSP by default, and more products will take advantage of GSP in future driver releases.
Offloading tasks which were traditionally performed by the driver on the CPU can improve performance due to lower latency access to GPU hardware internals.

The 58th annual edition of the TOP500 saw little change in the Top10. The Microsoft Azure system called Voyager-EUS2 was the only machine to shake up the top spots, claiming No. 10. Based on an AMD EPYC processor with 48 cores and 2.45GHz working together with an NVIDIA A100 GPU and 80 GB of memory, Voyager-EUS2 also utilizes a Mellanox HDR Infiniband for data transfer.

While there were no other changes to the positions of the systems in the Top10, Perlmutter at NERSC improved its performance to 70.9 Pflop/s. Housed at the Lawrence Berkeley National Laboratory, Perlmutter's increased performance couldn't move it from its previously held No. 5 spot.

NVIDIA (NASDAQ: NVDA) today reported record revenue for the second quarter ended August 1, 2021, of $6.51 billion, up 68 percent from a year earlier and up 15 percent from the previous quarter, with record revenue from the company's Gaming, Data Center and Professional Visualization platforms. GAAP earnings per diluted share for the quarter were $0.94, up 276 percent from a year ago and up 24 percent from the previous quarter. Non-GAAP earnings per diluted share were $1.04, up 89 percent from a year ago and up 14 percent from the previous quarter.

"NVIDIA's pioneering work in accelerated computing continues to advance graphics, scientific computing and AI," said Jensen Huang, founder and CEO of NVIDIA. "Enabled by the NVIDIA platform, developers are creating the most impactful technologies of our time - from natural language understanding and recommender systems, to autonomous vehicles and logistic centers, to digital biology and climate science, to metaverse worlds that obey the laws of physics.

The latest Tesla Model S comes with an infotainment system with serious gaming capabilities. EV manufacturers have turned their attention to making the infotainment systems of their vehicles a lot more capable, as they look to give car owners something to do whilst their vehicle fast-charges—a concept pioneered by the Honda e.

The new Model S infotainment system is a proper x86 PC powered by AMD Ryzen and custom AMD Radeon graphics. The GPU in particular, is based on the new "Navi 23" silicon powered by RDNA2 technology, and Elon Musk claims that the console offers performance rivaling a PlayStation 5 (which also uses an RDNA2-based graphics processor). The gaming-capable infotainment system is part of the $130,000 Plaid variant on the Model S. Its main touchscreen pivots into landscape mode. Meanwhile, images of a Tesla-branded game controller not unlike the one a PS5 comes with, surfaced on Reddit. It's unconfirmed if one of these comes included with the car, but it would make sense for a console-like controller to be the input device for games on this infotainment system, as a tablet-like touch interface would be sub-optimal with the fixed location of the screen.The recording of the Model S Plaid launch event follows.

Editor's note: This is not a part of April Fools.

NVIDIA has separated professional users and regular gamers with the company's graphics card offering. There is a GeForce lineup of GPUs, which represents a gaming-oriented version and its main task is to simply play games, display graphics, and run some basic CUDA accelerated software. However, what would happen if you were to start experimenting with your GPU? For example, if you are running Linux, and you want to spin a virtual machine with Windows on it for gaming, you could just use your integrated GPU as the GeForce card doesn't allow for virtual GPU passthrough. For these purposes, NVIDIA has its professional graphics card lineup like Quadro and Tesla.

However, this specific feature is about to arrive in even the GeForce lineup offerings. NVIDIA has announced that the company is finally bringing the basic virtual machine passthrough functions to the gaming GPUs. While the feature is representing a step in the right direction, it is still limited. For example, the GeForce GPU passthrough supports only one virtual machine and SR-IOV feature is still not supported on GeForce. "If you want to enable multiple virtual machines to have direct access to a single GPU or want the GPU to be able to assign virtual functions to multiple virtual machines, you will need to use NVIDIA Tesla, Quadro, or RTX enterprise GPUs.", says the NVIDIA FAQ. GeForce virtualization, which is now still in beta, is supported on R465 or higher drivers.The full content from NVIDIA's website is written below.

The third-generation semiconductor industry was impaired by the US-China trade war and the COVID-19 pandemic successively from 2018 to 2020, according to TrendForce's latest investigations. During this period, the semiconductor industry on the whole saw limited upward momentum, in turn leading to muted growth for the 3rd gen semiconductor segment as well. However, this segment is likely to enter a rapid upturn owing to high demand from automotive, industrial, and telecom applications. In particular, the GaN power device market will undergo the fastest growth, with a $61 million revenue, a 90.6% YoY increase, projected for 2021.

Driven by such factors as the continued development of autonomous driving technologies and the build-out of 5G infrastructure, the demand for automotive memories will undergo a rapid growth going forward, according to TrendForce's latest investigations. Take Tesla, which is the automotive industry leader in the application of autonomous vehicle technologies, as an example. Tesla has adopted GDDR5 DRAM products from the Model S and X onward because it has also adopted Nvidia's solutions for CPU and GPU. The GDDR5 series had the highest bandwidth at the time to complement these processors. The DRAM content has therefore reached at least 8 GB for vehicles across all model series under Tesla. The Model 3 is further equipped with 14 GB of DRAM, and the next-generation of Tesla vehicles will have 20 GB. If content per box is used as a reference for comparison, then Tesla far surpasses manufacturers of PCs and smartphones in DRAM consumption. TrendForce forecasts that the average DRAM content of cars will continue to grow in the next three years, with a CAGR of more than 30% for the period.

Cryptocurrency has in the past few years gained a lot of popularity, mostly fueled by Bitcoin's rapid growth and its massive price increasing over time. Today, Bitcoin, the world's leading cryptocurrency, has managed to make history and broke the record of 50,000 USD. As of now, on February 17th at 07:00 UTC, Bitcoin has reached 50,452.60 USD value. What is driving the price up you must wonder? It is the market adoption of the currency. Tesla Inc. has invested 1.5 billion USD in Bitcoin as it intends to accept it as payment for its products. Next up is Mastercard, which is preparing to support cryptocurrency on its network. In addition to Mastercard, Apple is also preparing its services for cryptocurrency payments. Right now, the market cap of Bitcoin is $935,359,977,182 at the time of writing, just shy of one trillion USD.

Today, Elon Musk, the founder of Tesla, Inc., has announced an update to the Tesla Model S automobile. The new car has seen a design revision for the first time since 2012, and it looks like something straight from the future. The interior has seen a complete revamp, and now it looks very futuristic and minimalistic. The specs of the car are also impressive. It can accelerate from 0-60 mph in just under two seconds. The starting price of the car is 80K USD, and it will be available in March. However, the speed and the price is not the main character found inside the car.

Tesla has announced that the updated Model S design has a new infotainment system that has a Tesla Arcade gaming platform with 10 TeraFLOPs of power. According to Mr. Musk, you will be able to play Witcher 3 and Cyberpunk on the Tesla Arcade, a new gaming platform for Tesla vehicles. Right now, it is undefined what is the exact configuration inside the new Tesla Model S car. However, it is speculated that AMD Radeon Navi 23 GPU is powering the platform. When it comes to the CPU choice, speculations are pointing out that Tesla is most likely using an Intel Atom chip paired with the aforementioned AMD Radeon GPU. All we know is that the GPU is clocked at 2.44 GHz, and possibly has 32 CUs. To play Cyberpunk and Witcher 3, you are would need to own one of these new Model S autos and the whole software stack is running locally. We are expecting to hear more about the final specifications once the car arrives in March.

The 56th edition of the TOP500 saw the Japanese Fugaku supercomputer solidify its number one status in a list that reflects a flattening performance growth curve. Although two new systems managed to make it into the top 10, the full list recorded the smallest number of new entries since the project began in 1993.

The entry level to the list moved up to 1.32 petaflops on the High Performance Linpack (HPL) benchmark, a small increase from 1.23 petaflops recorded in the June 2020 rankings. In a similar vein, the aggregate performance of all 500 systems grew from 2.22 exaflops in June to just 2.43 exaflops on the latest list. Likewise, average concurrency per system barely increased at all, growing from 145,363 cores six months ago to 145,465 cores in the current list.

If you are addicted to LAN parties and are a prosumer interested in purchasing a portable workstation that is a complete beast, then look no further. Media Workstations, a maker of all kinds of workstation PCs, has today launched a uniquely designed portable workstation called a-XP. Alongside its unique aesthetics, the PC is packing some serious hardware. At the heart of the machine, there lies AMD's Ryzen Thread Ripper 3990X CPU. With 64 cores and 128 threads, this makes the PC equipped with a huge CPU horsepower capable of handling any workload on the go.

Besides the speedy CPU, the chassis packs up to 256 GB of DDR4 2933 MHz memory, which is disturbed in 8 DIMMs of 32 GBs. There are options for two SSDs, and one HDD, which can go up to any capacity you specify. For GPUs, Media Workstations offers anything from NVIDIA GeForce RTX and Quadro RTX to Tesla GPUs. If you are crazy enough you can even put two of GPUs for workloads that benefit from dual-GPU setup. Be sure to check out the Media Workstations website for additional configuration details, here.

ASUSTek, the leading IT Company in server systems, server motherboards and workstations today announced the new NVIDIA A100-powered server - ESC4000A E10 to accelerate and optimize data centers for high utilization and low total cost of ownership with the PCIe Gen 4 expansions, OCP 3.0 networking, faster compute and better GPU performance. ASUS continues building a strong partnership with NVIDIA to deliver unprecedented acceleration and flexibility to power the world's highest-performing elastic data centers for AI, data analytics, and HPC applications.

ASUS ESC4000A-E10 is a 2U server powered by the AMD EPYC 7002 series processors that deliver up to 2x the performance and 4x the floating point capability in a single socket versus the previous 7001 generation. Targeted for AI, HPC and VDI applications in data center or enterprise environments which require powerful CPU cores, more GPUs support, and faster transmission speed, ESC4000A E10 focuses on delivering GPU-optimized performance with support for up to four double-deck high performance or eight single-deck GPUs including the latest NVIDIA Ampere-architecture V100, Tesla, and Quadro. This also benefits on virtualization to consolidate GPU resources in to shared pool for users to utilize resources in more efficient ways.

At its ambitious "Ampere" A100 Tensor Core processor reveal, the "Tesla" brand was nowhere to be seen. Heise.de reports that the company has decided to discontinue "Tesla" as the top-level brand for its HPC, AI, and scalar compute accelerator product line. NVIDIA introduced the Tesla compute accelerator brand along with its "Tesla" graphics architecture. It was the first major GPGPU product, and saw CUDA take flight as a prominent scalar compute language.

Over the years, NVIDIA kept the Tesla moniker as a top-level brand (alongside GeForce and Quadro), with an alphabetic portion of the model numbers denoting the graphics architecture the accelerator is based on (eg: Tesla P100 being "Pascal" based, K10 being "Kepler" based, and M40 being "Maxwell" based). The Tesla T4, based on "Turing," is the final product with the old nomenclature. Interestingly, Heise reports that NVIDIA dropped the name to avoid confusion with fellow Californian brand Tesla Inc.

Thanks to the sources of VideoCardz, we now have the first picture of the next-generation NVIDIA Tesla A100 graphics card. Designed for computing oriented applications, the Tesla A100 is a socketed GPU designed for NVIDIA's proprietary SXM socket. In a post few days ago, we were suspecting that you might be able to fit the Tesla A100 GPU in the socket of the previous Volta V100 GPUs as it is a similar SXM socket. However, the mounting holes have been re-arranged and this one requires a new socket/motherboard. The Tesla A100 GPU is based on GA100 GPU die, which we don't know specifications of. From the picture, we can only see that there is one very big die attached to six HBM modules, most likely HBM2E. Besides that everything else is unknown. More details are expected to be announced today at the GTC 2020 digital keynote.

NVIDIA is rumored to introduce their next-generation Ampere architecture very soon, at its GTC event happening on May 14th. We're expecting to see an announcement for the successor to the company's DGX lineup of pre-built compute systems—using the upcoming Ampere architecture of course. At the heart of these machines, will be a new GA100 GPU, that's rumored to be very fast. A while ago, we've seen NVIDIA register a trademark for "DGX A100", which seems to be a credible name for these systems featuring the new Tesla A100 graphics cards.

Today, NVIDIA's CEO was spotted in an unlisted video that's published on the official NVIDIA YouTube channel. It shows him pulling out of the oven what he calls "world's largest GPU", that he has been cooking all the time. Featuring eight Tesla A100 GPUs, this DGX A100 system appears to be based on a similar platform design as previous DGX systems, where the GPU is a socketed SXM2 design. This looks like a viable upgrade path for owners of previous DGX systems—just swap out the GPUs and enjoy higher performance. It's been a while since we have seen Mr. Huang appear with his leather jacket, and in the video, he isn't wearing one, is this the real Jensen? Jokes aside, you can check out the video below, if it is not taken down soon.Update May 12th, 5 pm UTC: NVIDIA has listed the video and it is not unlisted anymore.

NVIDIA updated its compute accelerator product stack with the new Tesla V100s. Available only in the PCIe add-in card (AIC) form-factor for now, the V100s is positioned above the V100 PCIe, and is equipped with faster memory, besides a few silicon-level changes (possibly higher clock-speeds), to facilitate significant increases in throughput. To begin with, the V100s is equipped with 32 GB of HBM2 memory across a 4096-bit memory interface, with higher 553 MHz (1106 MHz effective) memory clock, compared to the 876 MHz memory clock of the V100. This yields a memory bandwidth of roughly 1,134 GB/s compared to 900 GB/s of the V100 PCIe.

NVIDIA did not detail changes to the GPU's core clock-speed, but mentioned the performance throughput numbers on offer: 8.2 TFLOP/s double-precision floating-point performance versus 7 TFLOP/s on the original V100 PCIe; 16.4 TFLOP/s single-precision compared to 14 TFLOP/s on the V100 PCIe; and 130 TFLOP/s deep-learning ops versus 112 TFLOP/s on the V100 PCIe. Company-rated power figures remain unchanged at 250 W typical board power. The company didn't reveal pricing.