Manufacturing Bits: Sept. 17


Full-chip inverse lithography D2S has developed new hardware and software that enables a long-awaited technology--full-chip masks using inverse lithography technology (ILT). For years, ILT has been a promising technology. ILT is a next-generation reticle enhancement technique (RET) that enables an optimal photomask pattern for both optical and extreme ultraviolet (EUV) lithography reticles.... » read more

Machine Learning Inferencing At The Edge


Ian Bratt, fellow in Arm's machine learning group, talks about why machine learning inferencing at the edge is so difficult, what are the tradeoffs, how to optimize data movement, how to accelerate that movement, and how it differs from developing other types of processors. » read more

What’s Powering Artificial Intelligence?


While artificial intelligence (AI) and machine learning (ML) applications soar in popularity, many organizations are questioning where ML workloads should be performed. Should they be done on a central processor (CPU), a graphics processor (GPU), or a neural processor (NPU)? The choice most teams are making today will surprise you. To scale artificial intelligence (AI) and machine learning (... » read more

Nvidia’s Top Technologists Discuss The Future Of GPUs


Semiconductor Engineering sat down to discuss the role of the GPU in artificial intelligence, autonomous and assisted driving, advanced packaging and heterogeneous architectures with Bill Dally, Nvidia’s chief scientist, and Jonah Alben, senior vice president of Nvidia’s GPU engineering, at IEEE’s Hot Chips 2019 conference. What follows are excerpts of that conversation. SE: There are ... » read more

Week in Review – IoT, Security, Autos


Products/Services Rambus entered an exclusive agreement to acquire the Silicon IP, Secure Protocols, and Provisioning business from Verimatrix, formerly known as Inside Secure. Financial terms were not revealed. The transaction is expected to close this year. Rambus will use the Verimatrix offerings in such demanding applications as artificial intelligence, automotive, the Internet of Things, ... » read more

The Race For Better Computational Software


Anirudh Devgan, president of Cadence, sat down with Semiconductor Engineering to talk about computational software, why it's so critical at the edge and in AI systems, and where the big changes are across the semiconductor industry. What follows are excerpts of that conversation. SE: There is no consistent approach to how data will be processed at the edge, in part because there is no consis... » read more

Synthesizing Hardware From Software


The ability to automatically generate optimized hardware from software was one of the primary tenets of system-level design automation that was never fully achieved. The question now is whether that will ever happen, and whether it is just a matter of having the right technology or motivation to make it possible. While high-level synthesis (HLS) did come out of this work and has proven to be... » read more

Chiplets, Faster Interconnects, More Efficiency


Big chipmakers are turning to architectural improvements such as chiplets, faster throughput both on-chip and off-chip, and concentrating more work per operation or cycle, in order to ramp up processing speeds and efficiency. Taken as a whole, this represents a significant shift in direction for the major chip companies. All of them are wrestling with massive increases in processing demands ... » read more

Why Scaling Must Continue


The entire semiconductor industry has come to the realization that the economics of scaling logic are gone. By any metric—price per transistor, price per watt, price per unit area of silicon—the economics are no longer in the plus column. So why continue? The answer is more complicated than it first appears. This isn't just about inertia and continuing to miniaturize what was proven in t... » read more

Powering The Edge: Driving Optimal Performance With the Arm ML Processor


On-device machine learning (ML) processing is already happening in more than 4 billion smart phones. As the adoption of connected devices continues to grow exponentially, the resulting data explosion means cloud processing could soon become an expensive and high-latency luxury. The Arm ML processor is defining the future of ML inference at the edge, allowing smart devices to make independent... » read more

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