tag: AI

Packaging Technologies Redefine AI And HPC Scalability Limits At ECTC 2026
By Lori Scott - 05 Jun, 2026 - Comments: 0

The 2026 IEEE Electronic Components and Technology Conference (ECTC) showcased how advanced packaging can redefine the scalability limits of artificial intelligence (AI) and high-performance computing (HPC). Across 20 technical papers, Intel Foundry engineers and collaborators highlighted breakthrough innovations — from Embedded Multi-die Interconnect Bridge-T (EMIB-T) enabling large multi-d... » read more

Securing Terabit Ethernet For AI: Where MACsec, IPsec, And UET TSS Each Fit (And Why You Need More Than One)
By Vincent van der Leest - 04 Jun, 2026 - Comments: 0

As AI and HPC systems scale, the network has become both a critical enabler of performance and a rapidly expanding attack surface. The shift from rack-scale compute to cluster- and data center-scale AI infrastructure means that data is no longer confined to a single chip, board, or even system. Instead, it moves continuously across hundreds, or thousands, of endpoints, often at aggregate bandwi... » read more

The Edge LLM Offload Story
By Karthikeyan Shanmuga Vadivel - 04 Jun, 2026 - Comments: 0

By Karthikeyan Shanmuga Vadivel and Sauryadeep Pal Developers and system architects today face a growing demand to enable large language model variants on device. They are facing pressure to support transformer-capable models on constrained devices to ensure data privacy, eliminate cloud API charges, and provide offline reliability. On-device execution is also becoming a necessity to meet st... » read more

Toward Agentic Verification
By Brian Bailey - 28 May, 2026 - Comments: 1

Key Takeaways: Agentic verification provides flow orchestration for common repetitive tasks. Capabilities will expand when tools can learn from a larger context, including the specification. Design houses need to fully understand the costs and benefits and plan accordingly. Agentic verification is more than a buzzword. It is a pivotal moment in the evolution of verification ... » read more

Using SystemC TLM Modeling To Solve AI Data Movement Challenges
By Andy Nightingale - 28 May, 2026 - Comments: 0

In AI silicon, the performance numbers tell only part of the story. Marketing claims often highlight headline metrics such as trillions of operations per second, tensor throughput, matrix dimensions, and accelerator density. But engineers building these systems understand the harder truth. Compute performance matters only when data arrives at the right rate, with the right latency, and without ... » read more

Foundation Model For Physics: The Next Layer Of Intelligence For Engineering
By John Bruggeman - 28 May, 2026 - Comments: 0

Over the past decade or so, foundation models have emerged as the dominant paradigm for interacting with language, images, and code. Large Language Models (LLMs) can generate text. Vision models can interpret images. Multimodal systems can connect the two seamlessly. But one domain has not yet seen the same foundation-model-level shift: validated, deterministic reasoning over the physical wo... » read more

Faster Verification Debug With AI
By Taruna Reddy - 28 May, 2026 - Comments: 0

Every stage of semiconductor development takes longer and requires more effort with each new generation of chips. At no stage is this more apparent than functional verification. Industry consensus is that verification consumes roughly two-thirds of development time and resources. Within verification, debug is the most challenging step, consuming a third to two-thirds of the effort. Any serious ... » read more

Wafer-Scale vs. Chiplets: The New War? Part 1
By Nandan Nayampally - 28 May, 2026 - Comments: 0

Cerebras’ IPO is a meaningful moment for the semiconductor industry — and not just for the financial implications. Their confidence in their opening price reflects something the industry has effectively acknowledged: incremental chip scaling can no longer keep pace with what AI infrastructure demands. Radical approaches are earning serious consideration and serious capital. Cerebras... » read more

The Shape Of Prompts: Exploring Their Effect On Inference Infrastructure
By Amritam Putatunda - 28 May, 2026 - Comments: 0

AI inference prompts exhibit a shape-shifting behavior, arriving in many forms and attempting to fit themselves within the constraints of the inference stack. Ultimately, it is the design of the inference infrastructure that determines whether it can sustain a large volume of prompts or only a limited number. Prompts are not uniform transactions; they represent dynamic workload profiles whose ... » read more

Overcoming Bottlenecks In Data Movement
By Ed Sperling - 27 May, 2026 - Comments: 0

AI is all about data. There is more data to process, store, and move, and more tradeoffs required to do that efficiently and with enough flexibility to handle changes in future workloads. Nandan Nayampally, chief commercial officer at Baya Systems, talks about networks on chip and networks across chip, what the choke points are for data movement, and where and when data coherency makes sense. » read more

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