Achronix Semiconductor Corporation

Don't miss the #Chiplets: Building the Future of #SoCs virtual event on July 24 & 25! We’re thrilled to announce that Nick (Nicholas) Ilyadis, our in-house Chiplet expert at Achronix, will present his insights on FPGA-powered chiplet technologies. This event, hosted by EE Times | Electronic Engineering Times and embedded.com, will dive into technical trends, market demands, and new application areas around chiplet concepts, challenges, and technologies. ➡️ Register for free now: https://lnkd.in/e39__fG2 #ChipletsFutureofSoCs

Achronix was featured in SemiWiki.com's recent article discussing our webinar presentation with Embedded Computing Design on expanding AI capabilities in data centers. Find the insights shared by Viswateja Nemani, our Product Manager of AI & Software, and dive into the future of AI integration in the data center: https://lnkd.in/g4MtfWaZ

FPGAs are accelerating LLMs, and we have released benchmarks for the Llama2 70B model's performance📈: https://lnkd.in/gQcxYhfc With exceptional computational power and memory bandwidth, Achronix Speedster7t FPGAs are redefining what can be achieved with FPGA technology. Discover what you can accomplish with Achronix FPGAs.

Electronic Design published a new article by Scott Schweitzer, CISSP, Viswateja Nemani, Rob Latimer, and Jonnavithula ("Jon") Sreekanth about how the future of high-speed networking is being reshaped with our latest innovation in SmartNIC technology! Read the feature, "Redefining SmartNICs: The Composable Advantage," by William Wong available now in TechXchange 🔗 https://lnkd.in/gNzMFEwb Learn how our composable SmartNICs, powered by FPGA technology, are transforming packet processing and setting new benchmarks in the 400 GbE space. Get an inside look at how flexibility in packet processing can significantly boost your data center's efficiency and responsiveness. Set up a meeting with our team to learn more: https://lnkd.in/e2p7B4gm

Why choose Speedster7t FPGAs over GPUs for LLM inference? 🔗 https://lnkd.in/gwfQsmmR Our in-depth analysis shows a dramatic improvement in cost and energy per token. Perfect for developers and enterprises aiming to accelerate LLM inference applications. Read our full analysis for insights on enhancing your tech stack. 

Our partner, BittWare, highlighted the advantages of the Achronix 2D Network on Chip (NoC) technology in their latest article: https://lnkd.in/eVFS4rmf Why Achronix 2D NoC? It's all about smarter, faster, and more efficient FPGA design: 〰️ Seamless Connectivity: Our NoC replaces complex user-defined logic with a hard-wired network for less congestion and higher speeds. 〰️ Enhanced Efficiency: Simplify placement and routing while achieving target clock frequencies. 〰️ Direct Access & QoS: High-speed direct access to memories via PCIe and built-in Quality of Service for smoother resource sharing. 〰️ Comprehensive Coverage: The only NoC that spans the entire fabric and all peripheral interfaces, enhancing performance and reducing logic utilization. This distinctive capability allows for more efficient FPGA design, setting a new standard in the industry. Featured in BittWare’s St7-VG6 PCIe card, the Achronix Speedster7t FPGA showcases how our 2D NoC can significantly boost computing performance by improving logic separation and reducing internal congestion. Schedule a call with our FPGA experts to enhance your designs: info@achronix.com.

Speedster7t FPGAs are revolutionizing LLM inference! Our latest benchmarks reveal a 200% improvement in cost and power efficiency over GPUs when running the advanced Llama2 70B model. Explore the future of FPGA-accelerated large language models.  🌐 Learn more: https://lnkd.in/gQcxYhfc

New Product Brief Ready for Download ⏬: Bluespec, Inc RISC-V Soft Processors for Achronix FPGAs This new brief dives into the scalable programmability and customizability offered by integrating Bluespec’s RISC-V soft processors with Achronix’s cutting-edge Speedster®7t FPGA family. Discover how this partnership sets new benchmarks in FPGA design, offering: 🛠 Scalable and Flexible Processor Options: From single RISC-V processors to multi-core configurations, tailor your system to your precise performance needs. 📈 Enhanced Customization: Add custom instructions and accelerators to your design, enabling software management of hardware accelerators like never before. 🔄 Seamless System Integration: With the Achronix 2D network on chip (NoC), integrate multiple RISC-V cores effortlessly, boosting your design’s efficiency and performance. 🛠️ Complete Hardware/Software Stack: Equipped with full source code and packaged open-source toolchain, this solution kickstarts your development process with everything you need. Aimed at revolutionizing AI/ML acceleration, data center workloads, high-performance computing, and more, it is your gateway to unlocking unparalleled processing capabilities and efficiency. 🔗 Ready to transform your FPGA projects with the power of RISC-V? Download the product brief now and take the first step towards redefining programmable SoC designs. https://lnkd.in/gniAxJAW

Exciting news from our partners at iWave - iWave has launched the iW-RainboW-G64M System on Module (SoM), leveraging our Achronix Speedster7t AC7t1500 FPGA. This advanced SoM is engineered to propel high-performance AI/ML and high-bandwidth data acceleration applications to new heights. Key highlights of the iW-RainboW-G64M:  〰️ Compact form factor (120mm x 90mm) 〰️ Integrated 16GB GDDR6 and 8GB DDR4 memory 〰️ High-speed connectivity with 32 channels of SerDes up to 106Gbps 〰️ Embedded dual-core ARM Cortex processors for enhanced software flexibility This module simplifies FPGA-based design but also accelerates deployment across various sectors including AI/ML, networking, and data centers. By reducing PCB design complexities, developers can now focus on crafting tailored solutions more efficiently. We're excited to see how our technologies enable our partners and customers to push the boundaries of what's possible. For more details, read the full press release: https://lnkd.in/gmsTaQs4