High Performance Computing
High Performance Computing - HPC
VAMA is focused on HPCCs for Research and Development (R&D), Oceanographic, Medical Research, Mechanical, Aerospace and CAE application support and Educational divisions.
VAMA team has capability in implementing of variety of HPCCs that consists of two node cluster to multi-node / multi-core Clusters.
- CPU-GPU (Hybrid) HPCCs
CPU and GPU compute
Graphical Processing Unit (GPU) as a general-purpose computing unit, more and more HPC users are moving towards GPU-based clusters to run scientific and engineering applications.
The Workload Manager allows users to use a CPU and GPU together in a heterogeneous computing model, where the sequential part of the application runs on the CPU and the computationally intensive part runs on the GPU.
We offer a comprehensive solution & services on high performance computing with HPC Infra Design, Build, Optimization, etc.
We provide an optimized solution to use Parallel and/or Distributed computing techniques and applying it to the solution of computationally intensive applications across networks of computers
We have expertise in the following areas:
Performance, Scalability, and Consistency issues in File Systems.
Traditional Distributed File Systems.
Parallel Cluster File Systems.
Wide Area Distributed File Systems.
Cloud File Systems.
Commercial and Open Source File System Solutions.
The Application services are delivered by VAMA Industries Ltd to the customers empowering them to achieve their research goals. Our experts come with various solutions providing services like
Performance workflow improvement.
Performance tuning of Application.
Sizing of Storage Infrastructure.
Application analysis etc,.
Companies need to ensure that all their expensive HPC computing resources are being used wisely, from clusters to supercomputers to on- or off-premise cloud resources. In addition, these resources must be easy to use and manage. For this reason, HPC workload management is a critical component of any HPC system.
We have expertise in design, implementation and customization of various open source and commercial Workload managers Job scheduling software to intelligently assign workload to resources based on availability, priorities, policies, job requirements and other data
Workload manager to execute jobs (whether a large number of single-core jobs or a single, massively parallel job) and monitor progress on nodes in the system, managing completion of jobs and aggregating results
User-friendly graphical interfaces (GUIs) for submitting jobs, monitoring progress and displaying and analyzing job output