Embrace The New!


The ResNet family of machine learning algorithms was introduced to the AI world in 2015. A slew of variations was rapidly discovered that at the time pushed the accuracy of ResNets close to the 80% threshold (78.57% Top 1 accuracy for ResNet-152 on ImageNet). This state-of-the-art performance at the time, coupled with the rather simple operator structure that was readily amenable to hardware ac... » read more

Hardware-Based Methodology To Protect AI Accelerators


A technical paper titled “A Unified Hardware-based Threat Detector for AI Accelerators” was published by researchers at Nanyang Technological University and Tsinghua University. Abstract: "The proliferation of AI technology gives rise to a variety of security threats, which significantly compromise the confidentiality and integrity of AI models and applications. Existing software-based so... » read more

Hardware Security for Silicon Photonic-Based AI Accelerators


A technical paper titled “Integrated Photonic AI Accelerators under Hardware Security Attacks: Impacts and Countermeasures” was published by researchers at Ecole Polytechnique de Montreal and Colorado State University. Abstract: "Integrated photonics based on silicon photonics platform is driving several application domains, from enabling ultra-fast chip-scale communication in high-perfor... » read more

(Vision) Transformers: Rise Of The Chimera


It’s 2023 and transformers are having a moment. No, I’m not talking about the latest installment of the Transformers movie franchise, "Transformers: Rise of the Beasts"; I’m talking about the deep learning model architecture class, transformers, that is fueling anticipation, excitement, fear, and investment in AI. Transformers are not so new in the world of AI anymore; they were first ... » read more

Chiplets: Bridging The Gap Between The System Requirements And Design Aggregation, Planning, And Optimization


A technical paper titled “System and Design Technology Co-optimization of Chiplet-based AI Accelerator with Machine Learning” was published by researchers at Auburn University. Abstract: "With the availability of advanced packaging technology and its attractive features, the chiplet-based architecture has gained traction among chip designers. The large design space and the lack of sys... » read more

Nightmare Fuel: The Hazards Of ML Hardware Accelerators


A major design challenge facing numerous silicon design teams in 2023 is building the right amount of machine learning (ML) performance capability into today’s silicon tape out in anticipation of what the state of the art (SOTA) ML inference models will look like in 2026 and beyond when that silicon will be used in devices in volume production. Given the continuing rapid rate of change in mac... » read more

Operator Anxiety


Are you one of the early pioneers who have purchased an electric car? In the United States in Q3 2022, 6% of new vehicle sales were pure electric models. Despite all the hype — and significant purchase subsidies in support of battery cars — today only 1% of the cumulative number of vehicles in service in the US are purely plug-in electric. One of the reasons electric car sales have not full... » read more

Scalable Optical AI Accelerator Based on a Crossbar Architecture


A new technical paper titled "Scalable Coherent Optical Crossbar Architecture using PCM for AI Acceleration" was published by researchers at University of Washington. Abstract: "Optical computing has been recently proposed as a new compute paradigm to meet the demands of future AI/ML workloads in datacenters and supercomputers. However, proposed implementations so far suffer from lack of sc... » read more

Image Processing For Vision AI


Recent years have seen an increasing need for Vision AI applications using AI to enable real-time image recognition. Vision AI, which substitutes AI for human visual recognition, requires optimal image processing. Renesas has released RZ/V2M as mid-class, and RZ/V2L as an entry class, Vision AI microprocessors (MPUs). Both products are equipped with DRP-AI which is Dynamically Reconfigurable Pr... » read more

eFPGA Saved Us Millions of Dollars. It Can Do the Same for You


For those of you who follow Flex Logix, you already know that we have an IP business, EFLX eFGPA, and an edge inferencing co-processor chip and board business, InferX. InferX came about because we had many customers ask if they can run AI/ML algorithms in EFLX. The answer was and still is, of course you can – EFLX is an FPGA fabric similar to what FPGA chips use. Our co-founder, Cheng Wang, t... » read more

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