Here are two predictions by Gary Campbell, EVP Central Engineering and Richard Grisenthwaite, EVP Chief Architect, Arm

The future of AI

By Gary Campbell, EVP Central Engineering, Arm

“AI is fundamentally changing the way we live and work, and this transformation will only accelerate over the next 12 months – and well beyond that. In 2024, the conversation around AI will become more nuanced, focused on the different types of AI, use cases and – crucially – what technological foundation we need to put in place to make the AI-powered world of the future a reality.

Advanced, purpose-built chips will play a critical role in allowing today’s AI technologies to scale and in fueling further advancements in their deployment. The CPU is already vital in all AI systems, whether it is handling the AI workload entirely or in combination with a co-processor, such as a GPU or an NPU. As a result, there will be a heightened emphasis on the low power acceleration of these algorithms and the chips that run AI workloads in areas of intense compute power, like large language models, generative AI, and autonomous driving.

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By Dr. Larry Williams, Distinguished Engineer at ANSYS Inc. 

Dr. Larry Williams

Technological Innovations

There are a number of technological innovations that I predict will turn heads in 2024.

First, continued 3D-IC and heterogeneous integration. The slowing of Dennard Scaling and Moore’s Law can be mitigated in part by 3D-IC integration, but 3D-IC has several multiphysics challenges like thermal integrity, mechanical stress, and warpage. This is due to differential thermal expansion, electromagnetic modeling for signal integrity, and full-system power integrity. These trends drive the industry to add simulation of novel physical effects as part of integrated EDA workflows. Ansys RedHawk-SC Electrothermal offers a gold-standard technology platform to examine and simulate the multiphysics behavior of 2.5D and 3D-IC designs. Designers use it to model and analyze the full-system multiphysics of entire 3D-IC designs, including chip, interposer, package, and system boundary conditions. RedHawk-SC Electrothermal relies on core solver technology from trusted golden signoff tools including RedHawk-SC™, HFSS™, Icepak™, Ansys Mechanical™, and more, to provide a comprehensive workflow for the multiphysics challenges.

From these innovations, it’s clear that 3D-IC technology is driving an inflection point in semiconductor design, which has spurred Ansys and the entire EDA industry to retool with an expanded set of multiphysics capabilities that will still be undergoing rapid advances in 2024.

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By Ken Butler, Business Development Senior Director, Advantest Cloud Solutions (ACS)

Ken Butler

Most semiconductor market sectors saw a softening of business in 2023. However, 2024 should herald a rebound in demand. One driver will be the U.S. CHIPS and Science Act, which has already awarded its first contract as of this writing, and the similar efforts in other countries, each intended to minimize reliance on foreign sources within their respective semiconductor supply chains. Another part of that increase will be attributed to recent significant growth in the use of artificial intelligence (AI). In day-to-day life, there are many examples, such as AI-powered text and image generation, large language model (LLM)-enabled search engines from all the major providers, and AI productivity enhancers for many endeavors in STEM fields and others.

AI in Semiconductor Test

Semiconductor test is no exception to the infusion of AI technology into workflows and will also benefit from these new advances. In late 2023, Advantest announced the availability of the ACS Real-Time Data Infrastructure (RTDI), fueled by customer demand for adding complex AI/ML analytics to their test solutions. For all modern semiconductor products, but particularly for highly integrated “More than Moore” chiplet-based designs, product teams will continue to look for ways to incorporate advanced inferencing into the test process to optimize this valuable resource. Test optimization will be a frequent goal – every device should see “the right” test content – no more and no less than it needs. But today’s neural network-based techniques will also be used to detect devices that are quality or reliability risks, and should either be scrapped or have additional screening applied to ensure they will meet the demands of the end application and do so throughout the expected lifetime. Yield improvement will be another target, and AI will be applied to maximize product learning during the initial product ramp and into high-volume manufacturing. These inferences will increasingly be written in the languages favored by data scientists, such as Python, and made to run in concert with a test program written in a more traditional programming language.

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By Andreas Kuehlmann, CEO, Cycuity

Andreas Kuehlmann

Regulations and Vulnerabilities Make 2024 a Pivotal Year for  Semiconductor Chip Security

What 2024 Holds for Semiconductor Chip Security

Conversations around semiconductor chip security took place with greater frequency and prominence in 2023. Government legislation and newly discovered hardware vulnerabilities thrust the issue under the spotlight, and these developments will ensure hardware security remains a priority throughout 2024 and beyond.

The good news is that with so much at stake, the semiconductor industry is recognizing the need for more investments, accountability, and transparency. In 2024, we expect security will become a greater part of the design process, with higher priority given to adapting a comprehensive security design lifecycle ranging from developing verifiable security requirements, comprehensive security verification to documentation of security signoff.

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By Tora Fridholm, Corporate Marketing Manager at Codasip

In 2024, the tech scene is in for a shake-up and it’s all about customization and Custom Compute.

Technological Innovations / AI

AI’s shift to the edge is driving demand for custom accelerators, and RISC-V processors are stealing the spotlight. Companies designing AI platforms will be looking for differentiation as industry consolidation accelerates. Differentiation with unique algorithms will be augmented with customized processors for the specific software workloads. Meta openly talked about this at the RISC-V Summit (Nov. 2023) and more companies will make their plans public.

Codasip is investing in Custom Compute and using this technology to drive advances in AI for IP verification and design as well as technologies to drive end-user AI applications.
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By Pat Brockett, CEO, Celera Inc

Pat Brockett

Time for the Innovation Floodgates to Finally Open

Product innovation has accelerated over the past decade. Thanks to the widespread deployment if AI, there is now intelligence in just about every product we touch. These changes have improved our lives and saved some in the process. The trend seems to be unstoppable. But there is another side of what is happening all around us. It has to do with what is creating innovation, and what is enabling that innovation.

For many decades the chip industry led the way for innovation. A new processor from Intel or new cell phone platform from Qualcomm would define new markets and spur innovation. Over the past decade or so that’s changed. Now, software leads the way for innovation. New business models, new user experiences and all that intelligence we see in everything is defined by software.

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