AI explosion is clearly driving semi-industry since 2020. AI processing, based on GPU, need to be as powerful as possible, but a system will reach optimum only if it can rely on top interconnects. The various sub-system need to be interconnected with ever more bandwidth and lower latency, creating the need for ever advanced protocol… Read More
Artificial intelligence (AI) has revolutionized data center infrastructure, requiring a reimagining of computational, memory, and connectivity technologies. Meeting the increasing demand for high performance and efficiency in AI workloads has led to the emergence of innovative solutions, including chiplets, advanced… Read More
AI is exploding everywhere. We’ve all seen the evidence. The same thing is happening with AI conferences. The conference I will discuss here began in 2018 as the AI Hardware Summit. The initial venue was the Computer History Museum in Mountain View, CA. Like most things AI, this conference has grown substantially in a relatively… Read More
As the demand for higher performance computing solutions grows, so does the need for faster, more efficient data communication between components in complex multi-die system-on-chip (SoC) designs. In response to these needs, Synopsys has introduced the world’s fastest UCIe-based IP solution, capable of operating at a groundbreaking… Read More
The semiconductor industry is experiencing a significant transformation with the advent of chiplet design, a modular approach that breaks down complex chips into smaller, functional blocks called chiplets. A chiplet-based design approach offers numerous advantages, such as improved performance, reduced development … Read More
In the rapidly evolving landscape of high-performance computing (HPC) and artificial intelligence (AI), the demand for increased processing power, efficiency, and scalability is ever-growing. Traditional monolithic chip designs are increasingly unable to keep pace with these demands, leading to the emergence of chiplets… Read More
AI explosion is clearly driving semi-industry since 2020. AI processing, based on GPU, need to be as powerful as possible, but a system will reach optimum only if it can rely on top interconnects. The various sub-system parts (memory, processor, co-processor, network) need to be connected with interface links with ever more bandwidth… Read More
The increasing demands of data-intensive applications necessitate more efficient storage and memory utilization. The rapid evolution of AI workloads, particularly with Generative AI (GenAI), demands infrastructure that can adapt to diverse computational needs. AI models vary widely in resource requirements, necessitating… Read More
Artificial Intelligence (AI) continues to revolutionize industries, from healthcare and finance to automotive and manufacturing. AI applications, such as machine learning, deep learning, and neural networks, rely on vast amounts of data for training, inference, and decision-making processes. As AI algorithms become … Read More
The performance demands of data centers continue to grow, driven to large degree by the ubiquitous use of complex AI algorithms. On April 25, Embedded Computing Design held an informative webinar on this topic. Two experts looked at the problem from the standpoint of processor architecture and communication strategies, which… Read More
