Imagining A Hydrogen-Powered Future Thanks To Simulation


Our world leaders have set ambitious goals for global decarbonization by 2050, with good reason. While the planet continues to heat up, global energy consumption is still rising, and most of this energy consumption is currently derived from fossil fuels. This bitter truth has inspired a wave of decarbonization trends in response — including green hydrogen, which is generated using renewable ... » read more

Considerations For Accelerating On-Device Stable Diffusion Models


One of the more powerful – and visually stunning – advances in generative AI has been the development of Stable Diffusion models. These models are used for image generation, image denoising, inpainting (reconstructing missing regions in an image), outpainting (generating new pixels that seamlessly extend an image's existing bounds), and bit diffusion. Stable Diffusion uses a type of dif... » read more

Is Your Voltage Drop Flow Obsolete?


Voltage drop at advanced nodes is a deadly serious problem that has become unmanageable with the methodologies used by most chip designers today. This article will cover the reasons why power integrity has risen to a top-of-mind concern and why it has become almost impossible for today’s EDA tools to measure and fix it. We will then look at some radical methodology rethinking that is needed t... » read more

Damage Detection For Reliable Microelectronics


Over the past few years, the reliability and safety of electronic systems have become increasingly more important. Ongoing digitalization has made these systems an integral part of many items of daily use. This means that failures are becoming more and more critical as they can cause considerable disruption – even when they occur in consumer electronics. Today, electronics are also indispensa... » read more

Neural Network Model Quantization On Mobile


The general definition of quantization states that it is the process of mapping continuous infinite values to a smaller set of discrete finite values. In this blog, we will talk about quantization in the context of neural network (NN) models, as the process of reducing the precision of the weights, biases, and activations. Moving from floating-point representations to low-precision fixed intege... » read more

Reduce Data Center Over-Provisioning And Stranded Capacity For Sustainability


In the ever-evolving landscape of data centers, the issue of stranded capacity has become a significant concern for operators. Stranded capacity refers to the underutilization of resources. It is best referred to as the elephant in the data center due to the enormity of its impact. The losses are even more significant for the enterprise data center categories at above 40%. This outcome n... » read more

The Power Of HBM3 Memory For AI Training Hardware


AI training data sets are constantly growing, driving the need for hardware accelerators capable of handling terabyte-scale bandwidth. Among the array of memory technologies available, High Bandwidth Memory (HBM) has emerged as the memory of choice for AI training hardware, with the most recent generation, HBM3, delivering unrivaled memory bandwidth. Let’s take a closer look at this important... » read more

RTL Optimization Best Practices Help To Achieve Power Goals And Identify Reliability Issues Earlier


Designers face enormous challenges for low-power designs. Whether it is IoT at the edge, AI in the datacenter, robotics or ADAS, the demand for increased functionality and higher performance in SoCs is rapidly stretching power budgets to their breaking point. Power must be considered at every stage of chip design. Waiting to address power until late in the design cycle – post-netlist or durin... » read more

Can Software Testing Deliver ROI?


Innovation happens at a lightning pace, where software applications must follow suit or risk obsolescence. Consequently, quality assurance (QA) teams face a constant battle to ensure functionality, quality, and speed of release for their digital products. Software testing is critical to deliver in the face of this ever-increasing pressure. However, it is often seen as a burden, a cost center th... » read more

Unlocking The Power Of Edge Computing With Large Language Models


In recent years, Large Language Models (LLMs) have revolutionized the field of artificial intelligence, transforming how we interact with devices and the possibilities of what machines can achieve. These models have demonstrated remarkable natural language understanding and generation abilities, making them indispensable for various applications. However, LLMs are incredibly resource-intensi... » read more

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