TetraMem - Accelerate The World’s Post

#tetramem #devops Exciting News from TetraMem! 🚀 I am thrilled to share my company's latest achievement, a testament to the relentless pursuit of innovation by our team and esteemed research partners. I am reposting a post from our company about our most talented engineer, Wenbo Yin, whose recent publication in the *Science* journal marks a significant milestone in the field of analog computing, demonstrating our ability to perform scientific calculations with *arbitrary precision*. Following a breakthrough, which is an 11-bit device feature in *Nature* last year, this publication further establishes TetraMem as a pioneer in the tech industry. Our work showcases the potential of analog computing in revolutionizing data centers and enhancing computational accuracy for high-precision tasks. At TetraMem, we pride ourselves on our unique six-dimensional co-design and co-optimization approach, spanning from the manipulation of fundamental materials to the development of top-tier applications. This holistic strategy has not only facilitated our success in publishing in two prestigious journals but also positioned us at the forefront of addressing the increasing demand for computational power in AI and other advanced technologies. As we continue to innovate and push the boundaries of what's possible, our goal remains clear: to deliver cutting-edge technology that meets the evolving needs of our industry and society. Stay tuned for more updates as we strive to bring our advanced solutions to the market, aiming to make a tangible impact on the future of computing. I'd like to invite the community on LinkedIn to celebrate this remarkable achievement together! 🎉 To learn more about our groundbreaking work in analog computing and its implications, check out our latest publication in *Science*: [Programming memristor arrays with arbitrarily high precision for analog computing](https://lnkd.in/gMyq_xmw). #startup #startupgrowth #startuplife #startupcommunity #revenue #innovate #microcontroller #microprocessors #npu #ai #embeddedsystems #edgecomputing

We’re happy to share that our researchers Michael Roitzsch and Nils Asmussen will attend the ASPLOS (Architectural Support for Programming Languages and Operating Systems) conference in San Diego from 27th April to 1st May. Nils will present the paper “Towards Disaggregation-Native Data Streaming between Devices“ on Sunday 28th at the associated 3rd Workshop on Heterogeneous Composable and Disaggregated Systems (HCDS). The paper is about the integration of accelerator hardware in disaggregated data centers. Disaggregation is a trend in which you integrate computing resources such as accelerator hardware into your programs via a fast network in the data center. Accelerators such as GPUs and AI hardware are desirable because they perform certain tasks faster and more energy-efficiently than normal CPUs. However, the normal CPUs are still needed for two things: to execute the program logic and to coordinate the accelerators. Both together lead to the following problem: when integrating accelerators over the network, there are different options where to place the CPU with the software to coordinate the accelerators: either closer to the accelerator or closer to the program logic or somewhere in between. The paper explores three different options and compares them in terms of processing speed. Find the workshop program here: https://lnkd.in/dYMx2fdW

Lorentz butterfly simulation through analog computing: a chaotic behavior The shown circuit is not actually chaotic, as it lacks a negative resistor necessary to create chaotic behavior. Instead, this is a small analog computing block that solves the three Lorenz equations upon power-up of the circuit (notice there is no reset to the integrators). Lorenz was a meteorologist who significantly contributed to chaos theory. The Lorenz equations model atmospheric convection (a simplification) and, depending on the variable values, can exhibit chaotic behavior. This analog computing circuit solves these equations in real-time. The phase plane (XY plot) of the Z output vs. X output displays the Lorenz attractor, also known as the butterfly attractor, one of the well-known strange attractors. By the way, Lorenz coined the term "butterfly effect," referring to the idea that a tornado could be created by a butterfly flapping its wings weeks earlier. This exemplifies the sensitive dependence on initial conditions characteristic of chaotic systems. Chaos is not randomness but deterministic behavior that is highly sensitive to initial conditions. In chaotic systems, the state does not settle into a fixed point or predictable oscillation but continuously evolves in a manner that is extremely sensitive to initial conditions and hard to predict (as in the shown image). The circuit shown is based on the great work of Paul Horowitz ("The Art of Electronics" ). A tricky point of the schematic is understanding the reason for a division of 100 after the multipliers instead of 10.

Title: "Exploring Computer Organization and Architecture Basics" Description: Dive into the fundamental concepts of Computer Organization and Architecture in this enlightening video. Join us as we unravel the intricate layers that form the backbone of modern computing systems. From understanding the components of a CPU to exploring memory hierarchy and addressing modes, this video provides a comprehensive overview that will lay the groundwork for your journey into the world of computers. Whether you're a student or simply curious about how computers work, this video is a perfect starting point to grasp the core principles that govern the operation of digital devices. full video link - https://lnkd.in/gsdWQ382 #devlopement #coa #technology #ai #ml

I am working on the problem of a technological toolkit useful for finding the barriers and sorting through the mental leaps of understanding, that is, to approach "P versus NP" very low-key, and instead work on computer-assisted proof generally, as a way---the CUDA evolution included---some hands-on familiarity with the domain may inform a direction of research, etc. Between days spent theologizing, as well, I am up against the slowdown of that CUDA evolution, but hope is not lost, only it will take a complete overhaul probably so as not to waste clock cycles translating the data's representation into more machine-ready format. That is, some loops can be aborted early if in CPU land, but if determined first to copy that entire data set onto GPU-ready registers, it no longer benefits from the speedup. But I am hopeful, that the research will point the way for proper design in future projects (any thoughts on how to use several terabytes of storage?), design that is cognisant of what our computational paradigms are!

What simulator features help with learning quantum computing? Here is a minimal list, showcased in the video: - interactive UI to add a quantum gate, with a target, and control(s) - visualizing the state of the quantum system (a table with more info helps more than just a probability bar chart) - using color to ease the learning and build intuition - showing relevant steps in the building of a computation (the user can choose how big the steps are, based on their knowledge level) - visualizing the circuit/computation fragments, along with the updated state after each step The video shows an experiment with a single-qubit system. The current step and state are shown at the top, with all previous steps available for inspection by scrolling. At its heart, quantum computing is like any other computing that changes the state of a system through a simple set of instructions (and just like accounting). All computing professionals should be able to understand how to do it. #quantumcomputing #learning #simulation #visualization

🔍 Redefining the #Future of #Computing Before Quantum 🚀 In the midst of our collective anticipation for the breakthroughs Quantum Computing promises in the #DigitalTwin and #Simulation community, it's easy to overlook another imminent revolution: Massively parallel architectures and data flow processors surpassing todays architectures, including #GPUs. Though single-instruction, multiple-data (SIMD) paradigms aren't novel (they're the foundation behind GPUs powered #CFD solvers like #Simcenter STAR-CCM+), recent research advances in "novel" hardware architectures are turning heads. A standout example? #Google's latest blog on a fresh #ComputationalFluidDynamics framework leveraging their #TPUs by Shantanu Shahane 📰 https://lnkd.in/eMqvwSAU - A brilliant piece tracing its roots to a 2022 paper on #TensorFlow simulations: https://lnkd.in/eWndYPvY . But Google isn't alone: #Cerebras is making waves with real-time #ComputationalPhysics using wafer-scale Processors. Dive deep into Rob Schreiber's insights via his blog 📖 https://lnkd.in/emU_ZpBy or the corresponding paper 📑 https://lnkd.in/eA8uFx3d . #Groq and #Maxeler are exploring new architectural potentials with a unique twist on ML. Relive their insights, watch their results here 🎥 https://lnkd.in/erEMUgrD - inspired by foundational work from Stephan Hoyer and Michael Brenner. Pondering the future of computing beyond Moore's Law? John Shalf's 2020 perspective is a must-read: 📑 https://lnkd.in/eJQ-99gg . Though peering into the future is akin to gazing into a crystal ball, Shalf offers a compelling view on the timescale of emerging computing paradigms. I'm keeping a watchful eye on all possible paths. What are your thoughts on this future of computation? Let's discuss! 💬 #FutureComputing #BeyondQuantum #TechTrends Oskar Mencer, Tobias Becker

New open source library out! If you enjoy simulating OU processes check this out 😎  PS: you can also play around with thermodynamic algorithms for linear algebra with a scipy-like interface! 

I would be interested to see comments on this article. If it is accurate, this could represent a significant breakthrough. For my part, I would have like to see an actual example of a complex computation and how it is processed. https://lnkd.in/g2J6i4HN

😍 The QADA workshop is back! 💌 Join us at the "Quantum Algorithm Design Automation" workshop! @ IEEE International Conference on Quantum Computing and Engineering. ✨ After our hugely successful symposium of invited speakers last year, we're thrilled to announce a mix of invited talks and call-of-papers for this year's event. 📎 Submit your papers (2-6 pages) via EasyChair QCE24 (track WKS04-Workshop on Quantum Algorithm Design Automation). 🔮 As the quantum computing landscape rapidly evolves, the potential for solving problems deemed insurmountable by classical computers is on the horizon. The key to unlocking this potential lies in efficient quantum algorithm design in tandem with the hardware. The counterintuitive nature of quantum logic presents unique challenges. Traditionally, we've relied on quantum assembly language and qubit-level reasoning. Moreover, the complexity of quantum algorithms is soaring, underscoring the need for automation in algorithm design, programming, and compilation. Our dedicated workshop is a deep dive into the forefront of this research. If you're a quantum enthusiast, researcher, or developer passionate about shaping the future of computation, this workshop is tailor-made for you. Join us as we delve into the exciting realm of automated quantum algorithm design, programming, and compilation. 📆 Sunday, September 15th, 2024, 10:00 - 16:30 EDT 📍Palais des Congrès, Montréal, Québec, Canada 💡 Let's collaborate, innovate, and create a quantum-powered future together! 🌐 https://lnkd.in/gnFAyfc6 #QuantumComputing #AlgorithmDesign #Automation