Financial Service Industry HPC Cluster Introduction
What High-Performence Applications and Needs Are There in Financial Services?
High-performance applications and needs in financial services include real-time data processing, risk management, fraud detection, algorithmic trading, and high-frequency trading. These automated and personalized applications require high-speed computing, data storage, and networking capabilities to process large amounts of data quickly and accurately. Additionally, financial services organizations need to ensure that their systems are secure and compliant with industry regulations. HPC cluster networks provide the technology and infrastructure fundamental for these applications and requirements in the financial service industry.
Automated Business Processing, Conversational AI to Match Demand.
Faster Trading, AI-formulated Trading Strategies, Rapid Response to Markets.
Automated Claims Processing, Accelerated Analysis of Complex Case Processing.
Detect and Prevent Fraud, Improve AML & Understand Customer KYC Processes.
Personalized Interactive Services, AI Self-Service.
What Software Stacks Are Typically Used in Financial Service HPC Clusters?
Except for open-source software stacks, some specialized software is designed to meet the high-performance applications in financial services.
- NVIDIA Riva Conversational AI
- NVIDIA Merlin Recommendation System
- NVIDIA Rapids Accelerated Data
- NVIDIA Omniverse Digital Twins
- Apache Spark ETL tool
- Deep Learning Framework
- CUDA-Accelerated Library
What Hardware Are Typically Used in Financial Service HPC Cluster?
As we all know that financial services require high-performance and high-quality hardware to meet the low-latency, high-speed and high-bandwidth applications in real-time. This puts high requirements on the computing, storage and networking devices that are adopted in financial service HPC cluster data centers. For HPC computing and storage equipment, vendors like Intel, AMD, NVIDIA, HPE, etc. are popular choices; while for HPC optical connectivity assemblies, Mellanox was a common and usually the only pick. Here are the typically used server GPU and InfiniBand networking equipment for some specific needs.
Need Deep Learning & Data Processing & Predictive Analysis?
Recommended GPUs: A100/A30/A40/A10
Low-Latency Access to Storage, and Supports for GPUDirect RDMA & Network Security?
Use NVIDIA Mellanox InfiniBand NICs/DPU.
Need Connectivity Assemblies to Build Low-Latency and High-Performance InfiniBand Cluster?
Use 200Gb/s HDR InfiniBand active optical cables/passive copper cables/transceivers.