Category Archives: Cloud Servers

The world has seen a major shift to cloud computing, where companies use servers offered by big tech giants for their computing needs – Islander…

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Updated: July 21, 2024 @ 1:11 pm

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The world has seen a major shift to cloud computing, where companies use servers offered by big tech giants for their computing needs - Islander...

Amazon Graviton4 server CPU shown beating AMD and Intel processors in multiple benchmarks – TechSpot

In context: Amazon's AWS Graviton line of Arm-based server CPUs is designed by subsidiary Annapurna Labs. It introduced the processors in 2018 for the Elastic Compute Cloud. These custom silicon chips, featuring 64-bit Neoverse cores, power AWS's A1 instances tailored for Arm workloads like web services, caching, and microservices.

Amazon Web Services has landed a haymaker with its latest Graviton4 processor. They're exclusive to AWS's cloud servers, but the folks at Phoronix have somehow managed to get their hands on a unit to give us a peek at its performance potential.

Graviton4 packs 96 Arm Neoverse V2 cores, each with 2MB of L2 cache. The chip also rocks 12 channels of DDR5-5600 RAM, giving it stupid amounts of memory bandwidth to flex those cores. Positioning this offering for R8g instances, AWS promises up to triple the vCPUs and RAM compared to the previous R7g instances based on Graviton3. The company also claims 30 percent zippier web apps, 40 percent faster databases, and at least 40 percent better Java software performance.

However, the real story lies in those benchmarks, which the publication ran on Ubuntu 24.04. In heavily parallelized HPC workloads like miniFE (finite element modeling) and Xcompact3d (complex fluid dynamics), Graviton4 demolished not just its predecessors but even AMD's EPYC 'Genoa' chips.

One particularly impressive showing was in the ACES DGEMM HPC benchmark, where the 96-core Graviton4 metal instance scored a staggering 71,131 points, smoking the second-place 96-core AMD EPYC 9684X at 53,167 points.

In code compilation, the Graviton4 significantly outpaced the Ampere Altra Max 128-core flagship but lagged behind the varying core count Xeon and EPYC processors. However, it beat the EPYC 9754 in the Timed LLVM Compilation test.

The surprises kept coming with workloads not necessarily associated with Arm chips. Graviton4 demolished the competition in 7-Zip compression. Cryptography is another strong suit, with the Graviton4 nearly tripling its predecessor's performance in algorithms like ChaCha20.

After testing over 30 different workloads, Phoronix concluded that the Graviton4 is hands down the fastest Arm server processor to date. It's giving current Intel and AMD chips a considerable run for their money across various tasks.

Of course, this silicon arms race will only heat up further with new chips like Intel's Granite Rapids and AMD's Turin on the horizon. For now, AWS has a performance monster on its hands with Graviton4.

Image credit: Phoronix

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Amazon Graviton4 server CPU shown beating AMD and Intel processors in multiple benchmarks - TechSpot

Microsoft Servers Are Back After The World’s Biggest Outage Here’s What The Hell Happened – Pedestrian.TV

Thousands of businesses across Australia and the rest of the world are recovering after a massive IT outage caused chaos on Friday afternoon. But what exactly caused the outage, and is it likely to happen again?

Were aware of an issue with Windows 365 Cloud PCs caused by a recent update to CrowdStrike Falcon Sensor software, Microsoft said in a statement on X on Friday.

Massive disruptions that wreaked havoc on everything from radio and television, to banks and grocery stores after cybersecurity firm CrowdStrike pushed out a faulty content update on Windows servers. Servers running on Mac and Linux systems were not impacted by the outage.

CrowdStrike an American-based cybersecurity firm that offers a range of cloud-based security services to 538 of the Fortune 1000 companies launched the new update to its Falcon software on Friday, which caused a malfunction that disabled software worldwide. Ironically, the software is designed to protect against disruptions and crashes.

This system was sent an update and that update had a software bug in it and it caused an issue with the Microsoft operating system, CrowdStrikes CEO, George Kurtz told the US Today Show.

We identified this very quickly and remediated the issue, and as systems come back online, as theyre rebooted, theyre coming up and theyre working and now we are working with each and every customer to make sure we can bring them back online.

But that was the extent of the issue in terms of a bug that was related to our update.

If that wasnt enough, Microsofts own Azure cloud services also faced a major outage, causing even further issues for businesses. The two outages were unrelated, so I guess it was just a bad day for Microsoft.

The issue that prompted a blue screen of death for millions of users across the country was *not* the result of a cyberattack or hack so you dont have to worry about an ongoing threat to your security.

This is not a security incident or cyberattack. The issue has been identified, isolated and a fix has been deployed, Kurtz wrote on X. We refer customers to the support portal for the latest updates and will continue to provide complete and continuous updates on our website.

Kurtz added that customers remain fully protected, while apologising for the inconvenience and disruption.

Australian cybersecurity leader Alastair MacGibbon told the ABC that the issue wasnt malicious.

This is all about communication. This is about just reassuring the public that this doesnt appear to be a malicious act, MacGibbon said.

Of course, in slower time, it would be to try to understand how you could build systems to reduce the likelihood of this happening again.

You wouldnt be calling this a near miss. Its certainly a hit, but its a hit that wasnt malicious. And as a consequence, well learn more from it and therell be plenty of raking over the coals by government agencies and corporates all around the world.

At this point its probably easier to list the businesses that werent affected by the outage.

Low-cost airline Jetstar cancelled all Australia and New Zealand flights as a result of the outage, with flights only resuming at 2am on Saturday morning. Things should be largely back to normal today, but brace for delays if youre heading to the airport.

Jetstar said flights on Saturday are are currently planned to operate as scheduled. Please proceed to the airport as usual.

There may be a small number of flights impacted due to operational reasons. If your flight is impacted, we will communicate directly to you using the contact details on your booking, a statement on the Jetstar website read.

The outage also hit the airwaves, causing Triple J host Abby Butler to manually play the stations theme music out of her phone.

Self-serve checkouts and eftpos facilities at supermarkets and petrol stations also caused chaos, with some forced to close while others went cash-only.

Many major banks including Commbank and ANZ also had to close, which made getting cash out virtually impossible.

Rideshare services and delivery apps like Uber and Doordash also faced issues, which were likely caused by payment system outages.

The outage is being described as perhaps the biggest in history, but thankfully, it looks like it is already mostly resolved.

Deputy Secretary from the Home Affairs Cyber and Infrastructure Security Centre says the issue should self-resolve within the next hours and days.

There is no reason to panic, CrowdStrike are on it, it is not a cybersecurity incident and were working as fast as we can to resolve the incident, he said on X.

Most stores and services seem to be operating as normal on Saturday morning, with social media users reporting that even the Jetstar desk at Sydney Airport didnt look too manic.

It should go without saying that anyone catching a flight today should probably allow some extra time to avoid an airport-induced headache.

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Microsoft Servers Are Back After The World's Biggest Outage Here's What The Hell Happened - Pedestrian.TV

Cohesity goes epic on AMD Epyc – ComputerWeekly.com

Data security and management company Cohesity is following (if not leading) the infrastructure efficiency efforts being seen across the wider technology industry with recent work focused on energy-efficient computing.

Cohesity Data Cloud now supports AMD Epyc CPU-powered servers.

Epyc (pronounced epic) AMDs brand of multi-core x86-64 microprocessors based on the companys Zen microarchitecture.

The two firms have collaborated to make sure users can deploy Cohesity Data Cloud on AMD Epyc CPU-based all-flash and hybrid servers from Dell, Hewlett Packard Enterprise (HPE) and Lenovo.

Reminding us that organisations face challenges from ransomware and cyberattacks to stringent regulatory requirements, IT constraints, tight budgets and tough economic conditions, Cohesity says that to solve these challenges, companies need to take advantage of technology that is best suited to their specific requirements.

Customers each have unique needs but a common goal securing and gaining insight from their data. They trust Cohesity, in part, because we strive to offer the largest ecosystem with the most choices to suit their preferences, said John Davidson, group vice president, Americas sales, Cohesity.

By supporting AMD Epyc CPU-powered servers, Davidson says his firm is opening up new options for users to customise and modernise their datacenter.

[Customers can] increase performance and deliver energy, space and cost savings so they can execute their data security and management strategy on their preferred hardware configurations, he added.

All-flash servers have become an increasingly popular choice for organisations with high-demand applications and workloads, stringent power budgets for their datacentres, or increasing storage capacity requirements and little physical space within their datacentre.

As supermicro notes here, All-flash data storage refers to a storage system that uses flash memory for storing data instead of spinning hard disk drives. These systems contain only solid-state drives (SSDs), which use flash memory for storage. They are renowned for their speed, reliability, low energy consumption and reduced latency, making them ideal for data-intensive applications and workloads.

Cohesity now offers AMD-powered all-flash servers from HPE to modernise customer data centers and meet the requirements of green initiatives through the greater density, performance and cost savings all-flash servers provide over traditional servers.

Single-socket 1U HPE servers based on AMD Epyc can reduce the number of required nodes and power costs by up to 33% when compared with dual-socket 2U servers based on other CPUs.

Cohesitys AI-powered data security and management capabilities are now generally available on AMD-powered all-flash servers from HPE and hybrid servers from Dell and Lenovo.

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Cohesity goes epic on AMD Epyc - ComputerWeekly.com

AWS Graviton4 Benchmarks Prove To Deliver The Best ARM Cloud Server Performance – Phoronix

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This week AWS announced that Graviton4 went into GA with the new R8G instances after Amazon originally announced their Graviton4 ARM64 server processors last year as built atop Arm Neoverse-V2 cores. I eagerly fired up some benchmarks myself and I was surprised by the generational uplift compared to Graviton3. At the same vCPU counts, the new Graviton4 cores are roughly matching Intel Sapphire Rapids performance while being able to tango with the AMD EPYC "Genoa" and consistently showing terrific generational uplift.

Graviton4 reached general availability this week with initially powering the new R8g instances. Graviton4-based R8g instances are promoted as offering up to 30% better performance than the Graviton3-based R7g prior generation instances. Graviton3 CPUs sported 64 x Neoverse-V1 cores while Graviton4 has 96 x Neoverse-V2 cores based on the Armv9.0 ISA. The Neoverse-V2 cores with the Graviton4 have 2MB of L2 cache per core, twelve channel DDR5-5600 memory, and other improvements over prior Graviton ARM64 processors.

AWS promotes Graviton4 as offering up to 30% faster performance within web applications, 40% faster performance for databases, and 40%+ greater performance for Java software.

Being curious about the Graviton4 performance, I fired up some fresh AWS instances to compare the R8g instance to other same-sized instances. The "16xlarge" size was used across all testing for looking at 64 vCPUs each time and 512GB of memory per instance. The instances tested for today's article included:

Graviton2 - r6g.16xlarge Graviton3 - r7g.16xlarge Graviton4 - r8g.16xlarge AMD EPYC 9R14 - r7a.16xlarge Intel Xeon 8488C - r7i.16xlarge

All instances were tested using Ubuntu 24.04 with the Linux 6.8 kernel and stock GCC 13.2 compiler.

It would have been interesting to compere to Ampere Computing's cloud ARM64 server processors but not really feasible, unfortunately. With Ampere Altra (Max) in the cloud like with Google's T2A Tau instances, only up to 48 vCPUs are available. And even then Ampere Altra is making use of DDR4 memory and making use of Neoverse-N1 cores... AmpereOne of course is the more direct competitor albeit still not to be found. We still don't have our hands on any AmpereOne hardware nor any indications from Ampere Computing when they may finally send out review samples. Oracle Cloud was supposed to be GA by now with their AmpereOne cloud instances but those remain unavailable as of writing and Ampere Computing hasn't been able to provide any other access to Ampere One for performance testing. Thus it's still MIA for what may be the closest ARM64 server processor competitor to Graviton4.

Let's see how Graviton4 looks -- and its performance per dollar in the AWS cloud -- compared to prior Graviton instances and the AMD EPYC and Intel Xeon competition. The performance per dollar values were based on the on-demand hourly rates.

Page 1 - Introduction Page 2 - HPC Benchmarks Page 3 - Crypto Benchmarks, srsRAN + More Page 4 - Code Compilation + 7-Zip Page 5 - Ray-Tracing, Digital Signal Processing, OpenSSL Page 6 - Database Workloads - ClickHouse, PostgreSQL, RocksDB Page 7 - Blender + Conclusion

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AWS Graviton4 Benchmarks Prove To Deliver The Best ARM Cloud Server Performance - Phoronix

Oracle Drops After Musks xAI Shifts Away From Cloud Deal – BNN Bloomberg

(Bloomberg) -- Oracle Corp. dropped as much as 4.8% after Elon Musk said his artificial intelligence startup would rely less on cloud technology from the software maker, jeopardizing a potentially lucrative revenue stream.

In a post Tuesday on his social network X, Musk said his company, xAI, decided to build a system to train AI models internally because our fundamental competitiveness depends on being faster than any other AI company. The Information reported earlier that the companies had ended talks on a potential $10 billion cloud agreement.

Oracle Chairman Larry Ellison said last September that Oracle had a deal to provide cloud infrastructure to Musks xAI to train models. Ellison didnt release the value or the duration of the contract at that time. In Musks post, he said that xAIs Grok 2 model was trained on 24,000 Nvidia Corp. H100 chips from Oracle and is probably ready to release next month.

Musks decision to build AI-training infrastructure internally underscores the expansion challenges for cloud providers despite the availability of capital, wrote Anurag Rana, an analyst at Bloomberg Intelligence. We believe these issues extend beyond Oracle and could also vex Microsoft and AWS, not just because of a shortage in specialized chips, but also power.

In May, the Information reported that Oracle and xAI were close to a deal to expand their relationship. Musks startup would have spent about $10 billion to rent cloud servers from Oracle for a period of years, the Information reported then, citing a person involved in the talks. Those talks have now ended, the publication reported before Musks posts.

Oracles shares hit an intraday low of $138 after the report. The stock closed at $145.03 Monday, gaining 38% this year.

(Updates with post from Musk beginning in the second paragraph.)

2024 Bloomberg L.P.

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Oracle Stock Falls On Report That Talks Are Off For Cloud Deal With Elon Musk’s AI Startup – Investor’s Business Daily

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Northern Data Group to launch Europe’s first cloud service with Nvidia H200 GPUs Blocks and Files – Blocks & Files

Datacenter services outfit Northern Data Group will be the first cloud provider in Europe to offer the use of the recently launched powerful H200 GPU hardware from Nvidia.

Germany-headquartered Northern Data is made up of the Taiga Cloud, Ardent Data Centers, and Peak Mining business units. It will be Taiga Cloud that offers the GPUs in datacenters in the final quarter of this year, said Northern Data.

Northern Data Group is an Elite Partner of Nvidia. Taigas energy-efficient cloud is said to be powered by Europes largest cluster of Nvidia 100 Tensor Core and H100 Tensor Core GPUs, which helps organizations accelerate AI and ML innovation on demand, according to the company.

Taiga is deploying the new GPUs in partnership with Supermicro, and the move will help further build up Northern Datas high-performance computing solutions, while complementing its existing GenAI technologies available to customers.

The first full island of over 2,000 Nvidia H200 GPUs will deliver 32 petaFLOPS of performance, it is promised. They will utilize BlueField-3 data processing units (DPUs) and Nvidia Mellanox CX7 NICs. The configuration of Nvidia-referenced architecture will allow customers to access more bandwidth, and faster and more efficient data storage access, said the provider.

The GPUs will be accommodated in one of Northern Data Groups European datacenters, powered by carbon-free, renewable energy, and have a power usage effectiveness ratio of less than 1.2, it is promised.

Our GenAI platform is constantly evolving and we are proud to collaborate with Supermicro to be the first in Europe to offer access to Nvidia H200 GPUs, said Aroosh Thillainathan, founder and CEO, Northern Data Group. This is testament to our commitment to continually offer industry-leading, next-generation solutions.

We are collaborating with Northern Data Group to expand its GenAI cloud offering to include Supermicro GPU servers based on the latest Nvidia H200 HGX GPUs, added Vik Malyala, president and managing director, EMEA, and SVP of technology and AI at Supermicro.

We are fully committed to delivering the most performant and energy-efficient AI infrastructure and solutions, and this collaboration will accelerate availability and bring the best value for customers in Europe.

Last December, Ardent Data Centers revealed a 110 million ($119 million) investment to expand its ability to provide colocation services for HPC and AI compute power across both Europe and the US.

It signed Letters of Intent with two datacenter sites in the US, and was the preferred bidder on a strategic site in the UK. The assets will boost capacity to help address the surging demand for compute power needed for GenAI applications. The anchor tenant for the extra capacity will be sister company Taiga Cloud.

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Northern Data Group to launch Europe's first cloud service with Nvidia H200 GPUs Blocks and Files - Blocks & Files

Understanding serverless and serverful computing in the cloud era – TechRadar

Two distinct methods have emerged in cloud computing: serverless and serverful computing. Serverless computing represents a significant departure from traditional approaches, offering exciting possibilities for innovation, operational streamlining, and cost reduction. But what exactly does it involve, and how does it differ from the established serverful model?

Serverless computing introduces an approach where you, the developer, only worry about the code you need to run, not the infrastructure around it. This narrowing of focus simplifies operational management and cuts expenses by pushing the server management tasks elsewhere. As a concept, its similar to Business Process Outsourcing (BPO) or contracting out Facilities Management. Youre concentrating on the areas where you have IP or can build value and letting someone else own those non-core processes that extract value.

In contrast, Serverful computing is how most organizations have consumed the Cloud, where you are accountable for managing and overseeing servers while providing you with the most control and customization options.

Empowering IT professionals and developers with knowledge of these approaches and their inherent tradeoffs is crucial for devising an effective cloud strategy. Your expertise and understanding are key to choosing the right approach for your business.

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Serverful computing, or traditional server-based computing, involves a hands-on approach to deploying applications. In this model, you are responsible for managing the servers that run your applications, which includes provisioning servers, updating operating systems, scaling resources to meet demand, access control, and ensuring high availability and fault tolerance.

This approach provides more control over your IT infrastructure. You can customize almost every aspect of your environment to suit your application. For example, you can deploy additional security controls or software, tune the kernel to get maximum performance or use specific operating systems needed to support aspects of your application stackall of which arent readily achievable in a serverless environment.

On the other hand, Serverless computing takes most of the complexity away from managing cloud computing infrastructure by abstracting away the infrastructure. With this abstraction, you avoid directly managing cloud servers and instead hire backend computing in an as a service model. There are still servers, but you no longer need to worry about them; the provider ensures theyre available, patched, compliant, and secure.

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Serverless and Event-Driven computing are often used interchangeably, but whilst they overlap, there are some crucial differences.

Serverless computing can be used to implement event-driven architectures because it can automatically scale to handle a varying number of events and only charges for actual execution time. For instance, a serverless function can be triggered by an event such as an HTTP request or a message in a queue.

Not all event-driven architectures are serverless, and not all serverless functions are event-driven. Event-driven systems can also be built using traditional serverful infrastructure, and serverless functions can perform scheduled tasks or be invoked directly by an API rather than being driven by events.

There is no one-size-fits-all approach, and you may find that you use both options even within a single application. In an HR system, storing employee records in a serverful database is practical to support complex or long-running queries, such as payroll processing. However, multi-stage and ad-hoc time-off requests are well-suited for a serverless application.

Serverless computing offers two primary advantages: simplicity and an execution-based cost model. By adopting serverless, businesses can manage their infrastructure more easily, as the cloud provider takes care of server provisioning, scaling, and maintenance. This approach allows developers to focus on writing and deploying applications without the burden of managing underlying servers.

Serverless computing also enhances efficiency and resource utilization, as businesses only incur costs for the actual computing power used and when used. Business leaders can plan more simply because they know that each transaction costs and we expect , so our bill this month will be .

When used on platforms with open standards, for example, NATS.io instead of a Hyperscalers data-streaming solution, this transaction-based model can significantly reduce expenses and unlock new opportunities for innovation, freeing developers and managers to concentrate on building high-quality applications rather than dealing with infrastructure complexities.

On the other hand, serverful computing provides businesses with greater control and customisation over their infrastructure. By managing your servers, you can tailor their environment to meet specific needs and ensure high performance, reliability, and security. This approach is beneficial for applications that require consistent and long-term resource allocation, as it allows for fine-tuning and optimization that serverless models may not offer.

Additionally, serverful computing enables direct oversight of the hardware and software stack, enabling detailed monitoring and troubleshooting. This hands-on control can be crucial for enterprises with stringent regulatory requirements or those needing to handle sensitive data securely.

While serverless computing offers compelling benefits, it also presents challenges that businesses must navigate. On a smaller scale, being serverless is a highly efficient way to consume cloud computing services. When demand begins to ramp up, it can rapidly become costly, especially if platform lock-in is a factor. Think of it like taking a taxi versus buying a car. A taxi ride once a week is a cheap way to get home from the office, but taking a taxi to and from the office every day, to and from your kids school to drop them off or collect them, and to the shops at the weekend for groceries is going to quickly become outrageously costly when compared to buying a car.

To mitigate these risks, companies need to establish a culture of cost monitoring, open standards, and vendor evaluation. Choosing vendors with low or no egress fees can help control expenses, and using open standards ensures the app's portability. This avoids the risk of introducing technical debt by becoming overly reliant on a single provider's proprietary services or APIs. This will hinder flexibility and increase migration complexities down the line, potentially resulting in significant refactoring costs.

Balancing the advantages of serverless computing with these challenges requires careful planning and strategic decision-making to ensure long-term success in the cloud environment.

The decision here is how you manage the tradeoffs inherent in serverful and serverless computing: control vs consume, open standards vs proprietary, fixed costs vs dynamic cost base. Looking ahead to the next six months and beyond, serverless and serverful computing are poised to continue evolving in response to changing business needs.

While offering simplicity and cost-effectiveness, serverless computing remains constrained by factors such as speed and latency, much like other cloud-based services. However, many providers have built Edge and Distributed platforms that deliver more sophisticated serverless offerings, bringing computing power closer to end-users, mitigating latency issues and enhancing overall performance.

In contrast, serverful computing will maintain its relevance, particularly for applications requiring more significant control over infrastructure, higher performance, or specific regulatory or security requirements. There will always be a place for both serverless and serverful cloud computing. As cloud technology continues to mature, we may see advancements in serverful computing that improve automation, scalability, and resource optimization, further enhancing its appeal in certain use cases.

Ultimately, the future of cloud computing lies in striking the right balance between serverless and serverful approaches, leveraging the strengths of each to optimize performance, efficiency, security, and agility in an increasingly digital world.

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Apple Is Preparing M5 with SoIC for Future Macs and AI Servers – The Mac Observer

At WWDC last month, Apple finally announced its AI plans, which are expected to be the powerhouse of upcoming software updates including iOS 18, macOS 15 Sequoia, and so on.

Thats why Apple is gearing up to use more advanced and powerful chips, such as the M5 with SoIC (System on Integrated Chip) packaging to boost performance for both Macs and cloud-based AI servers. And once again, Apple will partner with Taiwan-based TSMC to meet its requirements, according to a report from Economic Daily.

As analyst Jeff Pu suggests Apples timeline may see AI servers equipped with the M4 chip by late 2025, potentially superseding current M2 Ultra chips used in AI cloud servers and originally designed for Mac devices. Meanwhile, hints about Apples upcoming M5 chip have already surfaced in official code, corroborating reports that work is ongoing, besides TSMCs 3nm process.

Apples AI cloud servers currently use several linked M2 Ultra chips, which were initially meant only for desktop Macs. When Apple switches to the M5 with SoIC, its advanced dual-purpose design suggests Apple is preparing for the future by integrating its supply chain to support AI across computers, cloud servers, and software.

TSMC introduced SoIC in 2018, letting chips stack up in 3D. This setup handles electricity and heat better than traditional flat designs. Apple and TSMC are teaming up to develop an even more advanced version of SoIC. Currently, its in testing, but the companies plan to start mass production of M5 for new Macs and AI servers by the second half of 2025.

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