Managing kW Power Budgets


Experts at the Table: Semiconductor Engineering sat down to discuss increasing power demands and how to address it with Hans Yeager, senior principal engineer, architecture, at Tenstorrent; Joe Davis, senior director for Calibre interfaces and EM/IR product management at Siemens EDA; Mo Faisal, CEO of Movellus; Trey Roessig, CTO and senior vice president of engineering at Empower Semiconductor.... » read more

Opportunities Grow For GPU Acceleration


Experts at the Table: Semiconductor Engineering sat down to discuss the impact of GPU acceleration on mask design and production and other process technologies, with Aki Fujimura, CEO of D2S; Youping Zhang, head of ASML Brion; Yalin Xiong, senior vice president and general manager of the BBP and reticle products division at KLA; and Kostas Adam, vice president of engineering at Synopsys. W... » read more

A HW-Aware Scalable Exact-Attention Execution Mechanism For GPUs (Microsoft)


A technical paper titled “Lean Attention: Hardware-Aware Scalable Attention Mechanism for the Decode-Phase of Transformers” was published by researchers at Microsoft. Abstract: "Transformer-based models have emerged as one of the most widely used architectures for natural language processing, natural language generation, and image generation. The size of the state-of-the-art models has in... » read more

Sensor Fusion Challenges In Automotive


The number of sensors in automobiles is growing rapidly alongside new safety features and increasing levels of autonomy. The challenge is integrating them in a way that makes sense, because these sensors are optimized for different types of data, sometimes with different resolution requirements even for the same type of data, and frequently with very different latency, power consumption, and re... » read more

Optimizing EDA Cloud Hardware And Workloads


Optimizing EDA hardware for the cloud can shorten the time required for large and complex simulations, but not all workloads will benefit equally, and much more can be done to improve those that can. Tens of thousands of GPUs and specialized accelerators, all working in parallel, add significant and elastic compute horsepower for complex designs. That allows design teams to explore various a... » read more

RISC-V Wants All Your Cores


RISC-V is no longer content to disrupt the CPU industry. It is waging war against every type of processor integrated into an SoC or advanced package, an ambitious plan that will face stiff competition from entrenched players with deep-pocketed R&D operations and their well-constructed ecosystems. When Calista Redmond, CEO for RISC-V International, said at last year's summit that RISC-V w... » read more

Week In Review: Design, Low Power


Arm filed its registration statement for a highly anticipated IPO. Chip industry heavyweights Apple, Samsung, NVIDIA, and Intel are all expected to invest. Find the SEC filing here. Taiwan’s National Science and Technology Council (NSTC) laid out a 10-year initiative to bolster its IC design market share to 40% worldwide by 2033, with the first year’s budget of US $376 million. The sh... » read more

AI Transformer Models Enable Machine Vision Object Detection


The object detection required for machine vision applications such as autonomous driving, smart manufacturing, and surveillance applications depends on AI modeling. The goal now is to improve the models and simplify their development. Over the years, many AI models have been introduced, including YOLO, Faster R-CNN, Mask R-CNN, RetinaNet, and others, to detect images or video signals, interp... » read more

SW-HW Framework: Graphic Rendering on RISC-V GPUs (Georgia Tech, Cal Poly)


A new technical paper titled "Skybox: Open-Source Graphic Rendering on Programmable RISC-V GPUs" was published by researchers at Georgia Tech, California Polytechnic State University-San Luis Obispo. Abstract Excerpt: "In this work, we present Skybox, a full-stack open-source GPU architecture with integrated software, compiler, hardware, and simulation environment, that enables end-to-end G... » read more

Complex Tradeoffs In Inferencing Chips


Designing AI/ML inferencing chips is emerging as a huge challenge due to the variety of applications and the highly specific power and performance needs for each of them. Put simply, one size does not fit all, and not all applications can afford a custom design. For example, in retail store tracking, it's acceptable to have a 5% or 10% margin of error for customers passing by a certain aisle... » read more

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