AMAX PDF One Pagers

AMAX PDF One Pagers
Table of Contents


On-Prem Retrieval Augmented Generation (RAG)

Summary:
The document discusses the advantages of Retrieval-Augmented Generation (RAG) for enterprise AI, highlighting its ability to customize Large Language Models (LLMs) for specific departmental needs. It emphasizes RAG's capability to provide real-time, relevant responses and enhance data protection, thereby increasing efficiency and informed decision-making within various departments.

Key Points:

  • RAG combines generative AI with advanced embedding techniques for precise, tailored responses.
  • Enables the customization of LLMs for different departmental needs, enhancing efficiency and decision-making.
  • Provides up-to-date insights with real-time, relevant information retrieval.
  • Offers enhanced in-house data protection and reliable performance, tuned specifically to business needs.

Sharpen Your Edge to Core Computing AMAX + Ufispace

Summary:
"Sharpen Your Edge to Core Computing" focuses on AMAX's collaboration with UfiSpace to advance AI deployment in Edge-to-Core computing. It highlights the complexities of managing core data infrastructure due to the influx of data from various edge systems and presents AMAX’s solutions that optimize resource use and performance from edge to core, facilitating open networking across multi-cloud environments.

Key Points:

  • AMAX's turnkey ecosystem efficiently extends from edge to core, optimizing resource use and performance.
  • Partnership with UfiSpace advances AI deployment capabilities in Edge-to-Core computing.
  • Products include Data Center Series, S9500 Series routers, and M3000-14XC Fronthaul Multiplexer (FHM), each offering unique benefits for network efficiency and service delivery.
  • AMAX solutions, like the Carrier Grade & short depth 3U server, are designed for high-performance workloads and feature the latest technology to enhance resilience, scalability, and network efficiency.

Crafting On-Premises AI Solutions - Intel Better Together

The document "Crafting On-Premises AI Solutions" from AMAX, in collaboration with Intel, outlines the development and implementation of advanced on-premises AI infrastructure to meet the growing demands of AI-driven enterprises for higher computing power and thermal management. Key insights include:

  • Emphasis on the necessity of robust on-premises AI solutions for supporting high thermal and power requirements of modern processors.
  • Custom-designed AI solutions powered by Intel® to ensure efficient management and real-time tuning of AI hardware resources.
  • The role of Intel® Xeon® Next-Gen Processors with built-in AI accelerators and advanced liquid cooling technology in enhancing data center capabilities.
  • AMAX's innovative approach to thermal management, including Direct-to-Chip (D2C) and immersion cooling, to address the challenges posed by powerful processors generating significant heat.

Performance measurement of a Hadoop Cluster

The AMAX Emulex Hadoop Whitepaper presents an in-depth analysis of Hadoop Cluster performance, emphasizing the significance of high-speed interconnects like 10Gb Infiniband in optimizing data processing tasks. This technical document delves into various aspects, from the challenges of Big Data to the specifics of Hadoop's architecture, offering insights into performance tuning and the role of AMAX's PHAT-Data solution in addressing Big Data acquisition, storage, and analysis issues.

  • Highlights the growing challenge of managing Big Data, with a focus on unstructured data's complexities.
  • Explores Apache Hadoop and MapReduce as pivotal technologies for processing vast data amounts, underlining the scalability and efficiency of Hadoop Distributed File System (HDFS).
  • Describes the configuration and benchmarks used to measure the Hadoop Cluster's performance, revealing the substantial benefits of 10Gb Ethernet interfaces in reducing execution times and enhancing throughput.
  • Concludes with the importance of network bandwidth in Hadoop workloads, advocating for the use of 10Gb interfaces for future-proof scaling and efficiency.

Pushing Operational Limits and Efficiencies with Liquid Immersion Cooling

AMAX, in collaboration with GRC, is transforming the datacenter landscape with its cutting-edge solution for liquid immersion cooling. This innovative approach leverages density-optimized GPU-accelerated servers and immersion cooling racks to deliver unparalleled computing power and energy efficiency. As the industry grapples with rising hardware density and costs, AMAX's solution not only pushes operational boundaries of CPU and GPU servers but also significantly reduces traditional datacenter construction costs.

  • Harnesses liquid cooling to handle rising hardware densities, offering a sustainable solution for CPU- and GPU-based servers.
  • Cuts traditional datacenter construction costs by roughly half, making high-performance computing more accessible.
  • Employs single-phase immersion cooling for optimized performance, achieving superior density and reducing total cost of ownership.
  • Offers a turnkey solution with the BrainMax™ ICG-160 server, specifically designed for immersion cooling, supporting up to 6 GPUs in a 1U chassis.

Deep Learning Performance and Cost Evaluation


The AMAX white paper compares Micron® 5210 ION SSDs against 7200 RPM HDDs in NAS setups for deep learning, showcasing SSDs' superior performance and cost-efficiency. It highlights an 11x performance boost with SSDs and up to 40% faster real-world application speeds, matching local NVMe drives. The study emphasizes QLC SSDs' balance between affordability and high performance, making them a viable solution for enhancing deep learning training without significant cost increases.

  • Demonstrates an 11x improvement in performance with QLC SSD array over HDD array in deep learning specific tests.
  • Reveals significant real-world application acceleration, with some cases up to 40%, aligning with local NVMe performance.
  • Highlights the cost-effectiveness of QLC SSDs for deep learning, offering a middle ground between HDD affordability and TLC SSD performance.
  • Suggests that NAS solutions built on read-intense QLC SSDs provide substantial, cost-effective performance gains for centralized training data repositories.