美光科技的动态

Great blog by Sudharshan Vazhkudai, Sarthak Thakkar, and Muktikanta Sa on the 5th Generation AMD #EPYC processor and Micron Technology’s DDR5 128GB RDIMM unleashing the power of #AI and database infrastructures. We make the world better together!!

An initial promise of the Compute Express Link (CXL) protocol was to put idled, orphaned memory to good use, but as the standard evolved to its third iteration, recent product offerings have been focused on memory expansion. Memory pooling with switch capabilities that speak to multiple servers was added later, and Jim Handy sees memory expansion being the more valuable capability. “If AI continues down its current path, it looks like the servers that do AI are going to need to have just huge, huge, huge memories on them,” he said. “CXL will be the way to serve that up to them.” https://lnkd.in/ggvsitDw

Are you running HPC and AI applications? Are your servers processing complex calculations at high speeds across multiple servers in parallel? Check out BeeGFS by ThinkParQ (the company behind BeeGFS): https://zurl.co/Cq8b BeeGFS is a hardware-independent parallel file system, optimized for high-performance computing. SupremeRAID? enhances the performance of BeeGFS — making it the ideal solution for HPC and AI applications. See the results: https://zurl.co/Cq8b #whitepaper #BeeGFS #HPC #AI #SupremeRAID #NVMe #serverstorage #NVMeSSD #datastorage #SSD #NVMeoF

?? Example: Applying Mathematical Analysis to Optimize Virtual Machines. Let’s say you're managing a server infrastructure where multiple virtual machines (VMs) are running simultaneously. A key challenge is to efficiently allocate resources (like CPU, memory, and bandwidth) to ensure that each VM performs optimally without overloading the system. Mathematical concepts such as optimization algorithms can be used to solve this problem. For instance: Linear Programming (LP): You can use LP to model resource allocation. The goal is to maximize the overall performance of the system, subject to constraints like available CPU cores, memory, and network bandwidth. - Objective Function: Maximize the total system throughput. - Constraints: Each VM has limited resources (e.g., max 4GB of RAM, 2 CPU cores). By solving this mathematical model, you can find the most efficient way to distribute resources among the VMs, ensuring high performance while minimizing costs. In real-world cloud platforms like AWS or Google Cloud, these types of optimization techniques are used to ensure efficient scaling and resource management, ensuring that the servers run smoothly without wasting resources. #virtual_machine #VMs #Mathematicalanalysis

X14 servers?from Supermicro offer maximum power and acceleration to support HPC workloads, large-scale AI training, LLMs, simulation, and more https://lnkd.in/g6mnAcxp #HPC #server #performance #X14 #LLM #AI

In the fast-paced realms of AI and machine learning, high-performance computing is essential. As Large Language Models (LLMs) grow more complex, organizations must decide: stick with the traditional method of connecting multiple servers with a few GPUs apiece via InfiniBand or Ethernet, or leverage GigaIO's SuperNODE, a single server boasting an incredible 32 GPUs? Learn more: https://bit.ly/4cDoY1b #GigaIOblog #LLM #HPC

Hammerspace has discovered how to add a GPU server’s local NVMe flash drives as a front end to external GPUDirect-accessed data sets. This is game changing for AI/HPC workloads. These onboard NVMe drives can speed up the AI/HPC workload by avoiding network latency and reducing the time it takes to checkpoint the AI/HPC workload progress by up to 90% or better. This is just another step towards making the GPUs run as close to 100% utilization as possible. To learn more, check out the link below, well worth the 4 minute read time. https://lnkd.in/dA6Pm-4G

Are you running HPC and AI applications? Are your servers processing complex calculations at high speeds across multiple servers in parallel? Check out ThinkParQ (the company behind BeeGFS) -- BeeGFS is a hardware-independent parallel file system, optimized for high-performance computing. SupremeRAID? enhances the performance of BeeGFS — making it the ideal solution for HPC and AI applications. See the results of our performance testing with GIGABYTE: https://zurl.co/oxu9 #whitepaper #BeeGFS #HPC #AI #SupremeRAID #NVMe #serverstorage #NVMeSSD #datastorage #SSD #NVMeoF

Your Data Center Just Got an Upgrade: Meet the AMD EPYC 9754 We’ve just received the incredible AMD EPYC 9754 processor, and it’s a true game-changer. With 128 cores and 256 threads, this powerhouse is designed to handle the most demanding workloads, from AI and machine learning to data-intensive applications. The EPYC 9754 delivers significant performance improvements, including faster VM deployment and better energy efficiency compared to previous generations. It also seamlessly supports mixed workloads, including HPC, analytics, and cloud-native applications. At Bytestock, we’re committed to keeping you ahead of the curve. Whether you’re scaling up your servers or tackling your next big project, the AMD EPYC 9754 delivers the performance and reliability you need to succeed. Ready to unlock maximum performance? Order today! ?? https://lnkd.in/eniwdrW7 #Bytestock #AMD #CPU #EnterpriseIT #TechInnovation #ServerUpgrades #DataCenter #DataCentreSolutions

?????? ?????????????? ???????????????? It is a pool of high-performance computing (HPC) or GPU instances that are connected with a high-bandwidth, ultra-low-latency network. These instances are managed as a group using instance pools. You would use cluster networks if you need to run a large-scale simulation that requires multiple identical HPC instances working together. ?????? ?????????????? ???????????????? It is a group of HPC, GPU, or optimized instances connected with a high-bandwidth, ultra-low-latency network. Compute clusters allow for more flexibility in managing instances. If you are running a dynamic workload that requires different types of instances, you would use a compute cluster. This allows you to add or remove instances as needed and manage them individually, providing greater flexibility. Both cluster networks and compute clusters leverage RDMA and RoCe for ultra-low latency communication, making them suitable for high-performance computing tasks. Are you eager to learn more? Check out, below links or DM me for more information. High Performance Computing: https://lnkd.in/deWT_Pj4 Cluster Networks: https://lnkd.in/dQ7GEqCc Compute Clusters: https://lnkd.in/deUJ8Bru #OracleCloud #OCI #CloudComputing #HPC #HighPerformanceComputing #ClusterNetworks #ComputeClusters #RDMA #CloudInfrastructure #DataCenter #CloudTechnology #CloudMigration #CloudArchitecture #EnterpriseIT #TechInnovation #CloudPerformance #ITInfrastructure #CloudSolutions #TechTrends2024 #CloudOptimization