HPC BIG DATA ANALYTICS COMPUTATION
High-Performance Computing (HPC) refers to the use of powerful computing systems and parallel processing techniques to perform complex calculations and data analyses at speeds far beyond those of standard computers. High-Performance Data Analytics combines HPC with data analytics to process and analyze large datasets rapidly. By utilizing parallel processing, HPC enables organizations to derive insights from data more quickly, supporting real-time decision-making and complex simulations.
HPC systems are essential for tackling large-scale problems in science, engineering, and business that require significant computational resources.
HPC involves aggregating computing power—often through clusters of interconnected computers, known as nodes—to achieve performance levels unattainable by individual machines. These systems are designed to process massive, multidimensional datasets and execute complex algorithms efficiently. For instance, while a typical desktop computer might perform billions of calculations per second, HPC systems can perform quadrillions of calculations per second, enabling tasks like real-time fraud detection or detailed climate modeling.
Core Components of HPC Systems
In conducting High-Performance Computing Analysis activities, an HPC system typically comprises three main components:
- Compute Nodes: Multiple high-performance processors or nodes that handle computation tasks.
- Network: High-speed interconnects that facilitate rapid communication between nodes.
- Storage: Scalable and fast storage solutions to manage large volumes of data.
These components work in unison to process complex workloads efficiently.
Applications of HPC
HPC is utilized across various domains, including:
- Scientific Research: Simulating physical phenomena, such as galaxy formation or molecular interactions.
- Engineering: Designing and testing prototypes through simulations, like crash tests for vehicles.
- Healthcare: Analyzing genomic data and modeling disease progression.
- Finance: Real-time risk assessment and fraud detection.
- Artificial Intelligence: Training large-scale machine learning models.
These applications benefit from HPC's ability to handle large datasets and perform computations at high speeds.
High-Performance Computing (HPC) Facility Specifications
| 1 * Master Node: Dell Power Edge R 730 | 6 * Compute Nodes: Dell Power Edge R730 with Intel Xeon Phi-coprocessor | 1 * Compute Node: Dell Power Edge R 730 with GPGPU Accelerator | 2 * Storage Nodes: Dell Power Edge R 730 |
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High-Performance Computation Services Price Schedule
The number and size of jobs allowed on PARAM KILIMANJARO may vary depending on user account/requirement. Below are the services offered by PARAM KILIMANJARO
- GPU: Graphical processing power
- CPU: General Purpose Computing
- Data storage/Processing/Analytic
- Hosting Services*
- Short course training
- Consultation services
Data Analysis Cost Matrix
| Account Type | Account Details | CPU Cores | RAM (GB) | Storage (GB) | 3 - Months | 6 - Months | 1 - Year |
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Staff Services
| Support Level | Description | Cost |
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General Support |
Limited code troubleshooting, training, office-hours. Once a week. |
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Advance Support |
Any time, any service |
$20 /per hour |
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Project Collaboration |
Percent time of a specific staff member charged directly to the grant |
%FTE |
