Astera Labs’ Post

Here’s an episode of a technical series Nonbox produced for FormFactor.

Powerful state of art CPUs and GPUs on HPCs alone cannot make simulations significantly faster.   Complex simulations need innovative algorithms that can give better result with HPCs with GPUs, simulations still consume significant time. The bottleneck? Outdated algorithms. BosonQ Psi (BQP) is revolutionizing simulation by introducing cutting-edge quantum-powered algorithms. Traditional algorithms developed three to four decades ago, have become obsolete, given the complexity and tech advancements. Not only do simulations take time, but some complex simulations cannot even be performed.   At BosonQ Psi (BQP), we are redefining the standards of simulation to harness the power of modern GPUs efficiently. Our quantum-inspired optimization algorithms are reducing simulations for optimizing designs significantly. 

OpenVINO™ integration with TensorFlow (OVTF) delivers OpenVINO™ inline optimizations and runtime needed for an enhanced level of TensorFlow compatibility. It is designed for developers who want to get started with OpenVINO™ in their inferencing applications to enhance inferencing performance with minimal code modifications. OpenVINO™ integration with TensorFlow accelerates inference across many AI models on a variety of Intel® silicon such as: Intel® CPUs Intel® integrated GPUs Intel® Movidius™ Vision Processing Units - referred as VPU Intel® Vision Accelerator Design with 8 Intel Movidius™ MyriadX VPUs - referred as VAD-M or HDDL

With AGI becoming prohibitively compute-hungry with the ever increasing number of parameters, and therefore suited for GPUs, especially for the model training task, how much longer before narrow-AI becomes suitable for CPU-based inference first and then expand to training? IEEE article from June 23 spoke of this case not being entirely dead, but a year later, where are we?

#AdvancedPackaging is enabling complex technologies that demand advanced testing techniques. In this video, we delve into the significance of testing thousands of chiplets used in CPUs, GPUs, HBM, I/O, and interposers on a single wafer. FormFactor's CEO, Mike Slessor, explains how the company is addressing these challenges with innovative testing solutions. https://lnkd.in/gy3nk6Vi

#Quantization reduces the precision of the numbers used to represent a model's parameters (weights and activations). This can be done entirely through software during the model training or post-training phases. The lower precision numbers require less memory and computational power, which translates into improved performance when the model is running. The hardware, such as CPUs, GPUs, or specialized AI accelerators, benefits from these optimizations as they can perform computations faster and more efficiently with lower precision data.

This #TechnicalThursday, we put Setonix GPU Power 💪 at your fingertips. Unlock the potential of AMD GPUs for your research on Pawsey's Setonix supercomputer with our Setonix GPU Partition Quick Start guide available in our documentation! 📄✨Learn how to: 🎛️ Access Setonix powerful AMD MI250X GPUs 🖥️ Run popular scientific applications 🚄Manage resources and submit jobs for peak performance This page will provide you with in-depth explanations, code examples, and valuable resources to unleash the full potential of Setonix GPUs. 📚Get Started Today: https://bit.ly/4bx1v0o #PawseySupercomputing #GPUs #ScientificComputing #AMD

Unlock the full potential of your AI workflows with Z by HP AI workstations. Equipped with pro-grade components like AI-accelerated GPUs, low-latency CPUs, high-speed memory & storage, and NPUs for sustained performance and battery life, these workstations are built to handle everything from content creation to model development. 🚀 #AI #MachineLearning #TechInnovation #ZbyHP #AIWorkstations #FutureOfWork

AMD's Latest Launch: Introducing Ryzen AI Mobile CPUs with Enhanced NPUs AMD’s innovation trajectory continues to impress as it unveils its latest generation of mobile CPUs, now branded as Ryzen AI. With the promise of up to 50 TOPS (Trillions of Operations Per Second) in neural processing power, these processors mark a significant leap forward in AI acceleration technology. The new CPUs, built on the third-gen Neural Processing Unit architecture dubbed XDNA 2, are integrated with upgraded CPU cores using the cutting-edge Zen 5 process. Alongside, there’s an enhanced integrated GPU, RDNA 3.5, offering a comprehensive solution for modern computing needs. https://is.gd/Mi5ugn #AI #AMD #artificialintelligence #Electronics #llm #machinelearning #RyzenAI