Even After 14 Generations, Intel’s 2023 “Meteor Lake” CPU will surprise you

Look out GPU makers!

Intel’s use of “Ray Tracing” (a rendering process lighting up a rendered scene by imitating how the human eye biologically sees light). That’s not easy but it allows the Si structures on tiled GPU circuits to “view” an artificial scene and render it as natural.

Now that processing demands enormously complex physics calculations WRT how light actually behaves. This is an amazingly ambitious Si engineering feat, from both computational tasking development and FAB wafer processing perspectives.

The impact on consumers should be felt in Gaming, Media Content Production, Streaming Server Processing, and other GPU intensive applications.

So, finally with the wave of 5G infrastructures being implemented around the globe, Cloud, Mobile and IoT implementations will provide an exciting “Game Changer” in our enjoyment of using technologies.

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US Gov Investment in Semiconductor Industry will drive Jobs, Construction and R&D.

Look for new CPU/GPU, Networking, Storage Silicon and Foundry Services Innovation!

With the passage of the US’ new “Chip Act 2022” the semiconductor industry will have access to huge sums funded by the Federal Government. These funds will be used to move manufacturing back on shore, create new jobs in operations and construction of FABs along with incentivizing R&D technology innovation.

The CHIPS Act’s investment tax credit and subsidies will be crucial steps to “bolster the semiconductor supply chain based in the United States and keep pace with industry incentives offered by other regions,” said Ajit Manocha, chief executive of trade group Semi, in a statement last week.

Biden Set to Sign Law to Pump $53 Billion Into US Chip Manufacturing

The semiconductor industry has been great for established companies like Intel, Samsung, AMD, Qualcomm and Nvidia, but the changing needs of applications, especially those in the data center, have created an opening for a new wave of startups that are creating new kinds of silicon solutions for compute, storage and networking.

New chip startups run the full gambit from general-purpose processors that can outperform Intel’s and AMD CPUs to accelerators that can speed up AI and deep learning workloads. Also, IDC is projecting global semiconductor revenue to continue growing in 2023 after years of pandemic-induced challenges, these semiconductor startups could benefit from what I once coauthored a “Think week’ paper about titled “When Moore’s Law is not Enough.”

Companies to watch in 2022-23:

Obviously, Intel, AMD, Nvidia and Qualcomm will benefit immensely from the Chip Act. However, these startups are taking on semiconductor heavyweights like Intel and Nvidia with new kinds of silicon solutions for compute, storage, and networking, many of which are headed for the data center. These are a few Si Enterprises to keep your eye on.

  • Ampere Computing targets Intel and AMD in the data center with Arm-based CPUs it says can outperform the competition. The Santa Clara, Calif.-based startup has Tencent, Bytedance, Equinix, CloudFlare and uCLoud as customers in addition to engagements with Microsoft and Oracle. The chipmaker also has OEM coverage beyond Gigabyte and Wiwynn to Foxconn and Inspur Group. The company designs its own custom cores for processors, going beyond its original strategy of using core designs from Arm for its 80-core Altra and 128-core Altra Max CPUs. The company’s CPUs are now publicly available in public instances provided by Oracle Cloud Infrastructure.
  • Cerebras Systems is targeting the AI compute market with its large Wafer Scale Engine 2 chip, that it calls the “largest AI processor ever made.” The Los Altos, Calif.-based startup announced WSE-2 chip — which comes with 2.6 trillion transistors, 850,000 cores and 40 GB of on-chip memory — and is “orders of magnitude larger and more performant than any competing GPU on the market.” The WSE-2 powers the startup’s purpose-built CS-2 AI system, which Cerebras says can deliver “more compute performance at less space and less power than any other system.” The startup’s systems have been adopted by the University of Edinburgh’s EPCC supercomputing center, GlaxoSmithKline, Tokyo Electron Devices as well as the U.S. Department of Energy’s Argonne National Laboratory and Livermore National Laboratory.
  • EdgeQ targets Intel and other players in the 5G infrastructure space with a new, AI-infused modem that can replace multiple components in a base station at a fraction of the cost. The Santa Clara, Calif.-based startup showed its synonymous “base-station-on-a-chip” 2021, promising a 50 percent reduction in total cost of ownership for 5G base stations over competing solutions. The startup showed off the RISC-V-based chip after emerging out of stealth mode in November of 2020 with $51 million in funding, and it has since added former Qualcomm CEO and Executive Chairman Paul Jacobs and former Qualcomm CTO Matt Grob as advisors. The EdgeQ chip can perform AI functions for edge computing applications while also using AI to improve network capabilities.
  • Fungible targets making hyperscale data centers available for any organization with its turn-key Fungible Data Center solution that is powered by its namesake data processing unit. With the already launched data center solution, the Santa Clara, Calif.-based startup claims it can easily slice and dice compute, storage, network, and GPU resources on demand while providing “performance, scale and cost efficiencies not even achievable by hyperscalers.” This is all made possible by the Fungible DPU, which can offload various functions from the CPU, including bare metal virtualization, software-defined networking, and local storage. The company has raised more than $300 million from investors, including a $200 million Series C round led by the SoftBank Vision Fund.
  • Mythic is targeting Nvidia and other AI chipmakers with its M1076 Analog Matrix Processor, which it says can deliver up to 25 tera operations per second of AI compute while requiring 10 times less power than a typical GPU or system-on-chip solution. The Redwood, Calif.-based startup introduced the M1076 AMP in a variety of form factors for servers and edge devices, saying it can tackle use cases ranging from video analytics to augmented and virtual reality. The launch of the new chip comes after the startup raised a $70 million funding round from Hewlett Packard Enterprise and other investors, bringing its total funding to $165.2 million.
  • Pliops targets data center storage economics with a hardware accelerator it says can “exponentially” improve cost, performance, and endurance for SSD storage. The San Jose, Calif.-based startup earlier this year announced it has raised a $65 million funding round led by Koch Disruptive Technologies, with participation from Intel Capital, Nvidia, Xilinx and Western Digital. The startup says its Pliops Storage Platform has been tested by more than 20 tier-one and enterprise companies, including database software vendor Percona, which said that the “Pliops storage processor is unique in that it is able to increase performance, improve compression and reduce write amplification.
  • Xsight Labs targets the data center switch market with a super-fast, programmable switch it says can meet the power and performance demands of cloud, high-performance computing and AI applications while also providing a flexible and scalable architecture. The Tel Aviv, Israel-based startup announced in March 2021 that it had raised a Series D funding round that was backed by several investors, including Intel Capital, Xilinx, and Microsoft’s venture fund, M12. The startup launched out of stealth mode in December 2020 with the announcement that it is now sampling X1, what it says is the industry’s first switch to offer up to 25.6 terabits per second in speed. The startup says its switch silicon offers these fast speeds at exceptionally low power, with less than 300 watts required for the higher end.
  • SambaNova Systems is targeting revolutionizing an integrated approach to AI computing with hardware, software and services that takes advantage of the startup’s Reconfigurable Dataflow Unit chip. The Palo Alto, Calif.-based startup announced it had raised a $676 million funding round led by SoftBank Group that also included the venture arms of Google and Intel. The startup is using the funding to grow market share against Nvidia and other competitors with its subscription-based Dataflow-as-a-Service AI platform, which relies on SambaNova’s RDU-based DataScale system to deliver what it says are “unmatched capabilities and efficiency” for AI.
  • SiFive is using an open-source alternative to target Arm’s CPU design business with core designs and custom silicon solutions for AI, high-performance computing and other growing markets based on the open and free RISC-V instruction set architecture. The San Mateo, Calif.-based startup has recently received takeover interest from multiple parties, including Intel, which has offered $2 billion to acquire the startup. Before the reported takeover interest, SiFive announced that Intel’s new foundry business, Intel Foundry Services, will manufacture processors using SiFive’s processor designs. Last August, the startup raised a $61 million Series E funding round led by SK Hynix, with participation from several other investors, including Western Digital Capital, Qualcomm Ventures, and Intel Capital. A month later, the company appointed former Qualcomm executive Patrick Little as its new CEO.
  • Tachyum is targeting Intel, AMD, Nvidia and other silicon compute vendors with what it calls the “world’s first universal processor,” which it says can replace the functions of CPUs, GPUs and other kinds of compute processors while providing higher performance and power efficiency. The Las Vegas-based startup announced that customers can now test its Prodigy processor with the company’s FPGA-based emulation system. A four-socket reference design motherboard is expected to be available this year. Tachyum claims that its Prodigy processor can run legacy x86, Arm and RISC-V binaries and outperform Intel’s fastest Xeon processors across data center, AI and high-performance computing workloads while consuming 10 times less power. The startup says Prodigy can also outperform Nvidia’s fastest GPU in AI and HPC workloads.
Top 10 Si Enterprises as August 2022
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