Argo Graphics Inc
Parallelization Strategy for High-speed Data Processing

Every year, many organizations are investing heavily in supercomputers, open-systems, and analytics for real-time data discovery. The introduction of high-end graphics in data processing based on large data analysis applications and graphic computation has escalated the need for HPC (High Performance Computing). Enterprises need ultimate computing acceleration for addressing a wide spectrum of challenges including augmented data processing, visualization, and adaptation in the simplest way. HPC is also witnessing its necessity for computer simulations that require intensive processing power for real-time results. With on-premise clusters assisting in computations and simulations, the CIOs prioritize on extending the reach to graphical computing with robust hardware. “HPC activities were focused on Symmetric Multiprocessing (SMP) server area through PC clusters and now extend to the recent General-Purpose Graphics Processing Unit (GPGPU) computation,” begins Muneshi Ozaki, President and COO, Argo Graphics.

Headquartered in Tokyo, Japan, Argo Graphics leverages parallelization and optimization technology through system design for enabling high-speed processing of large-scale technical computations. Any computation intensive program takes hours for completing the process. But with parallelization, a system can divide the task amongst the processors for reducing the total time taken for calculation. Argo Graphics provides HPC solution which incorporates parallelization of customer code. It ensures faster calculations by distributing the code in modules to different processors. This also enhances HPC system’s performance by deploying the file systems in a parallel manner. Complex calculations are also difficult to manage in a large HPC environment. The offering provides total management system for large scale computing.

Today, industries need real-time data on their dashboards for taking decisions instantly. However, deployment at industrial level needs reliability with high speed processing. Argo Graphics provides simulation solutions that are designed and engineered as per the requirement of particular industry. “In the public sector, we provide simulation systems including calculations of environment and atomic energies,” says Ozaki.

Argo Graphics provides solutions for parallelization of the in-house code of the specific customers to fit the latest architecture of the HPC systems using GPU

For distributing and managing data across multiple servers, customers in the HPC industry prefer Parallel File System. The company delivers services based on the parallel file system for its clients to manage their HPC systems efficiently. They also provide customization of the HPC management system through their service for ensuring an end-to-end customer experience.

To stay ahead of the curve, Argo Graphics ensures to meet customer’s demands in the computing space. Based on their needs, the company integrates tools like job scheduler and understands the system architecture with the manufacturer’s independent hardware selection. Argo Graphics has deployed parallel file system with these integrations for enhancing the performance of the system.

For successfully meeting the goal— ‘Grow with Customers’, Argo Graphics emphasizes on the computer device developers’ latest technologies. With the most advanced technologies on-board, the company configures the system as per the customer’s requirement. “Argo Graphics provides solutions for parallelization of the in-house code of the specific customers to fit the latest architecture of the HPC systems using GPU,” says Ozaki.

In the years to come, Argo Graphics seeks to deliver its solutions and services more efficiently and incorporate regular advancements for staying relevant amongst its competition. The company also envisions the democratization of HPC by bringing in the cloud technology to the industry. Forging ahead, Ozaki concludes with the company’s plan to focus on responding to the HPC market request from big-data analytics including machine learning or deep learning computing environment combined with cloud and on-premise hybrid infrastructure.