Surendra A.

Tackling Data Retention in SSDs (by Anil Burra from Intelligent Memory) 🤩 "SSDs have conquered the market due to their speed, durability, energy efficiency, and small form factor. However, write endurance and data retention are concerns in #embedded and #industrial applications, especially as the technology moves to ever smaller nodes." (Anil Burra) With the scaling of #NAND #flash #technology to higher densities (e.g., Triple-Level-Cell or Quad Level-Cell) and smaller process nodes, data retention becomes more challenging due to increased cell-to-cell interference and reduced margins for charge storage. Therefore, newer #technologies may have shorter specified data retention periods compared to older, more robust #SLC (Single-Level-Cell) or #MLC (Mul ti-Level-Cell) #NAND products. Two key factors affect data retention, the period over which #flashmemory can store #data without loss or corruption, in #NANDflash cells: program/erase (P/E) cycling and operating temperature. A very big thank you to Anil Burra from Intelligent Memory for this insightful article via Electronic Specifier Ltd with more background and insights via the link below 💡🙏👇 - A very good read to an important TOPIC 🤩 https://lnkd.in/eqdH7-N2 #semiconductorindustry #semiconductormanufacturing #innovation #it #ai #ssd #datastorage #automotiveindustry #embeddedsystems #ic #computer #computing #iot #memory #chip #chips #technology #tech

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Jim Keller, former Intel, AMD, and Tesla engineer, aims to challenge Nvidia's dominance in AI with Tenstorrent's energy-efficient chip design. Tenstorrent's upcoming second-generation AI chip promises superior energy and cost efficiency, presenting a viable alternative to Nvidia's offerings. The innovative design of Tenstorrent's chip features independent decision-making cores, potentially reshaping AI chip technology across diverse applications. #AI #Nvidia #semiconductor #semiconductors #chip #technology #innovation #research #computing Tenstorrent NVIDIA https://lnkd.in/g6a3vAu4

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In the fiercely competitive semiconductor industry, companies are in a constant battle to retain top talent because in the heart of every good engineer is a passionate problem solver, looking for their next challenge. For them, innovation is the currency of success. Yet companies like Qualcomm, Intel, and Broadcom attract tens of thousands every year by dangling lucrative compensation packages to lure them from competitors. Startup leaders don’t have those resources, so they have to work harder to attract the best talent and then fight like hell to retain them. But some of the most successful startup leaders I know take a different approach. Rather than viewing attraction and retention as a fight, they leverage the inherent qualities of their companies as their advantage. They use their nimbleness, bias toward innovation, and their collaborative cultures like superpowers to attract the right people and those usually end up being the reasons why people stay. Take Richard Fung, CEO of The Six Semiconductor, for example. I had a conversation with Richard and asked him to share his approach to motivating his team. His response was like a mini-masterclass on the topic of talent attraction and retention. Richard emphasized that a culture that encourages engineers to dive deep into the intricacies of their craft, understand the systems they’re building, and connect with the end customer is a successful culture. Richard has been using this approach and it's been paying dividends for The Six Semiconductor so in his honor, here are his six key concepts for creating this type of organization: 1. Foster a Learning Culture: Support ongoing learning and skill development beyond employees' core responsibilities. 2. Prioritize Customer Focus: Embed a customer-centric mindset, and encourage employees to enhance user experiences through their work. 3. Champion Problem-Solving: Empower employees to creatively solve challenges with a focus on customer needs. 4. Promote System-Level Understanding: Encourage employees to grasp the bigger picture of the company's offerings and their role within it. 5. Break Down Silos: Promote collaboration to ensure a comprehensive understanding of projects across teams. 6. Offer Meaningful Challenges: Provide intellectually stimulating projects that make a tangible impact on the company's success. What Richard highlighted is that success goes much deeper than getting great people to join. It's about unleashing the full potential of every individual on your team to drive innovation and help shape the company, and ensuring your team heads in the right direction together. I’m thrilled I got to learn Richard’s perspective and believe other leaders can benefit from hearing it, so I shared the video below. My "challenge question" to other startup leaders is this: what are you doing to foster this type of culture in your organization? Either share below or, feel free to DM me. #semiconductorindustry #startup #leadership

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In this episode of the "Quick Chip Series" on the Semiconductor Leadership Podcast, we dive into the remarkable journey of Qualcomm, a powerhouse in the semiconductor industry. On Youtube: https://lnkd.in/de6CY2Jw On Spotify: https://lnkd.in/dppbZi5C Join us as we uncover surprising facts and lesser-known stories about the company's rise to prominence. Did you know Qualcomm's name was almost different? What unexpected innovation sparked its success? How did a single invention revolutionize mobile communication forever? Tune in to discover these intriguing details and more. Subscribe to our YouTube and Spotify channels now to stay updated with our latest episodes and never miss an insight into the semiconductor world!

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#Memory Production Utilization Near Full Capacity, Surpassing Mature Nodes Foundries 💡 As memory prices and demand rise, memory manufacturers Nanya Technology and Winbond have resumed normal production, no longer reducing output as they did last year. TrendForce Corporation and industry sources cited in a report from Liberty Times Net also indicate that memory shipments will continue to recover in the third quarter. Reportedly, memory manufacturers’ utilization rates have reached 90% to 100%, surpassing the 60% to 70% utilization rates of mature process foundries. Last year, in response to market conditions, #Winbond adjusted its inventory and reduced production at its Taichung plant by up to 30-40%. This year, as market demand has rebounded, production has resumed, with capacity now at full utilization, producing 58,000 #wafers per month. Moreover, Winbond’s #Kaohsiung plant has introduced new capacity equipment, increasing monthly production from 10,000 to 14,000 wafers and upgrading processes from 25nm to 20nm. #Nanya Technology adjusted production levels dynamically last year, reducing output by up to 20%. However, production has gradually increased this year. Thanks again to TrendForce 集邦科技 for the full article with more background and insights via the link below 💡🙏👇 https://lnkd.in/eKPUUCis #semiconductorindustry #semiconductors #dram #datacenter #pc #it #ai #smartphone #notebook #mobile #taiwan #industrial #technology #tech

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Concerns arise over Intel Corporation's competitiveness in manufacturing advancements, as Broadcom's evaluation indicates that the 18A process may not be ready for high-volume production. Despite Intel reporting a reasonably healthy defect density rate for the 18A process, it faces challenges in meeting customer expectations, particularly from significant clients such as Broadcom. #semiconductor #technology #wafer #18A #research #semiconductors #semiconductortechnology #innovation #market #wafer https://lnkd.in/dyCTT8Yy

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Should Lattice Semiconductor buy Altera? With no product portfolio overlap, both companies can strengthen each other. Intel needs a cash injection, selling Altera would be a great way to do that quickly. For Lattice, this would leap frog them into the next tier. Combined revenue would be ~$2.2B, still smaller than AMD's Xilinx hence SEC should not have an issue with it. Before anyone says a smaller company buying a larger one, remember Avago's acquisition of Broadcom? This marriage would be great for the employees, customers, industry, and both companies.

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PCIe Gen6 + 5nm + MRVL SerDes = Lowest Power for AI!!

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Hyperscale network operators need more and more distance from their network. In this video, Stephen Adolph, Associate Vice President, Coherent DSP Product Line Management at Marvell, highlights the advanced Probabilistic Constellation Shaping (PCS) technology that allows a distance of up to 1,000 kilometers at 800 Gbps for DCI links. This simultaneously keeps the cost of scaling networks down while extending capabilities for higher reach and higher capacities. Watch the video to learn more about the technology and why it’s so important in today’s marketplace.

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🔍It’s no mystery: there's no #AI without #hardware. As AI continues to help solve great mysteries from the ocean to space, here’s one I can help solve: custom chip #tech is mission-critical for the #future of AI. Unpack more insights in #ConnectingAI: https://lnkd.in/gw3jBcuJ #artificialintelligence #machinelearning

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Nvidia and Intel go way back. They had kindof a truce where they stuck to their own markets. But PCIe decided otherwise. Xeon was using PCIe gen3 while AMD Epyc was already on PCIe gen4. Nvidia was used to integrate Xeons all the time. In return, Intel never brought out a discrete GPU to directly compete with Nvidia as AMD was doing. Then the PCIe thing happened, and if anything is crucial it is the bandwidth of the PCIe link between CPU and GPU. Similar to the stage where Intel wasn't interested in low power cpus (phones and tablets where ARM was allowed to grow into a giant), this truce hampered Intel. So they only started to develop a discrete GPU after the relationship took a hit. Of course they had the on chip gpu but that is just minimal in comparison with the beasts we got from AMD and Nvidia. In hindsight, everything is quite obvious, the truce worked for a long time. And not going low power probably made sense back then for whatever real reason. I'm just observing to understand more about the complex nature of semi giants and their strategies. For make benefit great person myself. https://lnkd.in/gqBMYDWi

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As #AI technology continues to grow, hardware solutions must keep up. #AI has the potential to solve real problems facing communities. I, for one, am excited to be a small part of helping develop  #technology that can change our world for the good. Read more in Connecting AI #58: https://lnkd.in/g7WTXyE2 #artificialintelligence #machinelearning

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now #RISC-V going after the very top end of CPU cores courtesy SiFive https://lnkd.in/ghpnsnQm Arm has some serious upcoming competition to its nascent entry into servers AMD and Intel Corporation (despite the latter's difficulties in the present) aren't merely going to roll over and leave it to #ARM and whatever space can be taken away from legacy software systems running in x86, RISC would be waiting moreover, #RISCV has a unique advantage - accelerator designers can augment the hardware with custom instructions

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In this bonus episode - "Free Gold - Understand the value you represent ... The Power of Impenetrable Confidence" in my Semiconductor Leadership Podcast Series. We are close to 1,500 subscribers in just under 3 months. I think we can do 2,000 by the summer. Please subscribe if it is of value to you: https://lnkd.in/diktXgVg In this exclusive bonus episode of the Semiconductor Leadership Podcast, we delve into the often underestimated power of confidence in the high-stakes world of BUSINESS. Discover how to have that impenetrable confidence to shape perceptions, influence decisions, and drive innovation in this fiercely competitive industry. We’ll explore a real-world scenario whereby someone experiments by handing $2,000 worth of gold for free to the random public and where confidence has been a game-changer where you can discuss strategies to build and project this essential quality, and analyze its impact on perceived value both within a company and in the market at large. Tune in to gain insights that could redefine how you lead and succeed in the semiconductor realm. Robert Quinn Ksenia V. Mia Chen

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BREAKING:Nokia's Strategic Acquisition of Infinera: A Game-Changer for Optical Networks as two Optica Corporate Members merge. In a significant move to bolster its network infrastructure business, Nokia has announced its acquisition of optical networks company Infinera, valuing the deal at $2.3 billion. This acquisition marks Nokia's second major shake-up in its Networks Infrastructure division within a single day. Nokia anticipates that the acquisition of Infinera will be a crucial driver towards achieving a double-digit operating margin for its Optical Networks business, which is one of three units in the revamped Networks Infrastructure division. The deal is expected to enhance Nokia's operations in North America, a region that underperformed in Q1. The acquisition offer stands at a 28% premium on Infinera's closing share price as of June 26, comprising at least 70% in cash and up to 30% in stock. Nokia emphasized that 60% of Infinera's revenue is generated from North America, with the acquisition expected to strengthen Nokia's position in the optical sector across APAC, EMEA, and Latin America. Pekka Lundmark, President and CEO of Nokia, remarked, "Now is the right time to take a compelling inorganic step to grow our optical capabilities, following our commitment to organic growth in 2021. The combined businesses have a strong strategic fit given their highly complementary customer, geographic, and technology profiles." Federico Guillén Moñino, President of Network Infrastructure at Nokia, added, "We have long respected Infinera as a competitor, but now we find the logic of combination irresistible." Nokia projects that the acquisition will expand the scale of its Optical Networks business by 75%, providing opportunities to accelerate product development and enhance its competitive edge. Key benefits expected include an expanded digital signal processor development team, expertise in silicon photonics, indium phosphide-based semiconductor materials, and advanced photonic integrated circuit technology. The acquisition is slated to close in the first half of 2025, pending approval from Infinera shareholders and regulatory authorities. With all this in mind watch Light Reading Video analyst Sterling Perrin and Infinera CEO David Heard discussing at the recent OFC Conference how the AI traffic boom is already driving optics in data center interconnect, subsea and terrestrial telecom networks, and also open new opportunities for Infinera’s chips inside the data center itself. Interesting numbers in that interview. https://lnkd.in/dKBz57Pa

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Some great commentary about the industry consolidation in generative AI. Worth reading.

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100,000 #H100 Clusters: Power, Network Topology, Ethernet vs InfiniBand, Reliability, Failures, Checkpointing 💡Frontier Model Scaling Challenges and Requirements, Fault Recovery through Memory Reconstruction, Rack Layouts There is a camp that feels #AI capabilities have stagnated ever since GPT-4’s release. This is generally true, but only because no one has been able to massively increase the amount of compute dedicated to a single model. Every model that has been released is roughly GPT-4 level (~2e25 FLOP of training compute). This is because the training compute dedicated to these models have also been roughly the same level. In the case of Google’s Gemini Ultra, NVIDIA Nemotron 340B, and Meta LLAMA 3 405B, the FLOPS dedicated were of similar magnitude or even higher when compared to GPT-4, but an inferior architecture was utilized, resulting in these models falling short of unlocking new capabilities. While OpenAI has gotten more #compute, they have mostly directed it at bringing smaller, overtrained, cheaper to inference models such as GPT-4 Turbo and GPT-4o. OpenAI admits they only just started training the next tier of model recently. The obvious next step for #AI is to train a multi-trillion parameter multimodal transformer with massive amounts of #video, #image, #audio, and text. No one has completed this task yet, but there is a flurry of activity in the race to be first. Multiple large AI labs including but not limited to OpenAI/Microsoft, xAI, and Metaare in a race to build #GPU clusters with over 100,000 GPUs. These individual training clusters cost in excess of $4 billion of server capital expenditures alone, but they are also heavily limited by the lack of #datacenter capacity and power as #GPUs generally need to be co-located for high-speed chip to #chip networking. A 100,000 GPU cluster will require >150MW in datacenter capacity and guzzle down 1.59 terawatt hours in a single year, costing $123.9 million at a standard rate of $0.078/kWh. A very big thank you again to Dylan Patel , Daniel Nishball, CFA and SemiAnalysis for the full article with more background, charts and insights via the link below 💡🙏👇 https://lnkd.in/eM_CBmM8 #semiconductorindustry #semiconductors #semiconductors #technology #tech #innovation #artificialintelligence #foundry #tsmc #datacenter #it #ai #cloudcomputing #computing #computer #hpc

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#AI truly can help even the playing field. Whether it is translating a meeting into a participant's native language in real time or helping match shoppers with high-quality retail experts, #genAI is changing the way we do things. In today’s #ConnectingAI #53 we explore how customized hardware will propel these advanced #AI tools forward: https://lnkd.in/gvyXqnwB #artificialintelligence #machinelearning

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#Intel Vs. #Samsung Vs. #TSMC #Foundry competition heats up in three dimensions and with novel technologies as planar scaling benefits diminish 💡 The three leading-edge #foundries — Intel, Samsung, and TSMC — have started filling in some key pieces in their roadmaps, adding aggressive delivery dates for future generations of #chip #technology and setting the stage for significant improvements in performance with faster delivery time for custom designs. Unlike in the past, when a single industry roadmap dictated how to get to the next process node, the three largest #foundries increasingly are forging their own paths. They all are heading in the same general direction with 3D #transistors and packages, a slew of enabling and expansive technologies, and much larger and more diverse ecosystems. But some key differences are emerging in their methodologies, architectures, and third-party enablement. Roadmaps for all three show that transistor scaling will continue at least into the 18/16/14 angstrom range, with a possible move from #nanosheets and forksheet FETs, followed by complementary FETs (CFETs) at some point in the future. The key drivers are #AI / #ML and the explosion of #data that needs to be processed, and in most cases these will involve arrays of processing elements, usually with high levels of redundancy and homogeneity, in order to achieve higher yields. A big thank you again to Ed Sperling and Semiconductor Engineering for the full article with more background and insights via the link below 💡🙏👇 https://lnkd.in/eWbsgkMs #semiconductorindustry #semiconductormanufacturing #tech #it #chips #innovation #semiconductors #taiwan #southkorea #usa #japan #ai #iot #automotivetechnology #adas #datacenter #computer #it #germany

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