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More Efficient Matrix-Multiplication Algorithms with Reinforcement Learning (DeepMind)


A new research paper titled "Discovering faster matrix multiplication algorithms with reinforcement learning" was published by researchers at DeepMind. "Here we report a deep reinforcement learning approach based on AlphaZero for discovering efficient and provably correct algorithms for the multiplication of arbitrary matrices," states the paper. Find the technical paper link here. Publis... » read more

Architecting Faster Computers


To create faster computers, the industry must take a major step back and re-examine choices that were made half a century ago. One of the most likely approaches involves dropping demands for determinism, and this is being attempted in several different forms. Since the establishment of the von Neumann architecture for computers, small, incremental improvements have been made to architectures... » read more

Improving Medical Image Processing With AI


Machine learning is being integrated with medical image processing, one of the most useful technologies for medical diagnosis and surgery, greatly expanding the amount of useful information that can be gleaned from scan or MRI. For the most part, ML is being used to augment manual processes that medical personnel use today. While the goal is to automate many of these functions, it's not clea... » read more

EDA Vendors Widen Use Of AI


EDA vendors are widening the use of AI and machine learning to incorporate multiple tools, providing continuity and access to consistent data at multiple points in the semiconductor design flow. While gaps remain, early results from a number of EDA tools providers point to significant improvements in performance, power, and time to market. AI/ML has been deployed for some time in EDA. Still,... » read more

Software-Hardware Co-Design Becomes Real


For the past 20 years, the industry has sought to deploy hardware/software co-design concepts. While it is making progress, software/hardware co-design appears to have a much brighter future. In order to understand the distinction between the two approaches, it is important to define some of the basics. Hardware/software co-design is essentially a bottom-up process, where hardware is deve... » read more

Monitoring Performance From Inside A Chip


Deep data, which is generated inside the chip rather than externally, is becoming more critical at each new process node and in advanced packages. Uzi Baruch, chief strategy officer at proteanTecs, talks with Semiconductor Engineering about using that data to identify potential problems before they result in failures in the field, and why it's essential to monitor these devices throughout their... » read more

11 Ways To Reduce AI Energy Consumption


As the machine-learning industry evolves, the focus has expanded from merely solving the problem to solving the problem better. “Better” often has meant accuracy or speed, but as data-center energy budgets explode and machine learning moves to the edge, energy consumption has taken its place alongside accuracy and speed as a critical issue. There are a number of approaches to neural netw... » read more

Roadblocks For ML in EDA


Is EDA a suitable space for utilizing machine learning (ML)? The answer depends on a number of factors, including where exactly it is being applied, how much support there is from the industry, and whether there are demonstrable advantages. Exactly where ML will play a role has yet to be decided. Replacing existing heuristics with machine learning, for example, would require an industry-wide... » read more

Tradeoffs To Improve Performance, Lower Power


Generic chips are no longer acceptable in competitive markets, and the trend is growing as designs become increasingly heterogeneous and targeted to specific workloads and applications. From the edge to the cloud, including everything from vehicles, smartphones, to commercial and industrial machinery, the trend increasingly is on maximizing performance using the least amount of energy. This ... » read more

The Other Side Of AI System Reliability


Adding intelligence into pervasive electronics will have consequences, but not necessarily what most people expect. Nearly everything electronic these days has some sort of "smart" functionality built in or added on. This can be as simple as a smoke alarm that alerts you when the batteries are running low, a home assistant that learns your schedule and dials the thermostat up or down, or a r... » read more

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