Firms that use traditional workstations are limited by the throughput of one single machine. This causes resource limitations with data store performance, storage, and network bandwidth. Grid computing reduces the bottlenecks caused by these limitations by allowing data to be spread across multiple servers. Cloud grid computing goes further by adding an extra element of elasticity to the underlying technology resources. Hentsū partners with Google Cloud Platform (GCP) to leverage BigQuery, which is a fully managed data warehouse that analyzes Big Data at heightened speeds, allowing for interactive analysis of massive datasets while remaining highly scalable and secure.

Data store performance

Fully managed, serverless databases enable you to analyze large datasets quickly, without the need to deploy, update, configure, or manage your database solution. Additionally, data processing patterns are managed and executed on your behalf including ETL, batch computation, and continuous computation.

PC Processor/memory/storage

Different applications and workloads require different storage and database solutions. Cloud grid computing makes storage scalability easy and cost efficient while featuring a consistent API, latency, and speed across storage classes. GCP offers three types of object storage that supports all types of workloads and unstructured data.

Network bandwidth

Rather than being limited to the network bandwidth of a single server, grids can be assembled over a wide area, using a varied collection of server and CPU types or by “borrowing” spare computing cycles from otherwise idle machines.

Challenges of running a cloud environment

Cloud grid computing does not come without its challenges. The radically different processes have made cloud computing one of the largest technological disruptions to hit enterprise computing since the advent of the PC. New firms are in prime position to move directly into the cloud, whereas existing firms face the challenge of migrating legacy systems and tools to the new cloud infrastructure, which takes additional forethought and planning. Clearly, understanding the workloads and the target cloud architectures helps to avoid the many pitfalls of misapplied cloud technologies. When cloud based data needs to be moved between services or regions, there are some considerations to be made around internal network speeds and overall architecture. This reiterates the principles around proper assessment, starting small and growing strategically.

Hentsū Solutions

What is needed is an agile way of solving these resource bottlenecks using new technology architectures. The Hentsū vision is to deliver hedge fund technologies that are agile, secure, compliant, scalable, resilient and cost effective. Hentsū builds solutions that maximise the benefit offered by cloud infrastructure providers like GCP for hedge funds. Tell us about the technology challenges that you face – we would love to hear from you: hello@hentsu.com For more information on Cloud grid computing and its benefits, join us at our upcoming New York event on January 25thhttps://hentsuprod.wpengine.com/events/infinitely-scalable-clusters/

Date/Time

Date(s) - 01/01/1970
12:00 AM - 12:00 AM

Location

600 5th ave. NY, NY

How do you process your research workloads?

Do you still use dedicated workstations or do you farm out to worker node clusters? It’s no question that grid computing is the future for research; firms moving away from traditional workstations to the grid not only experience lower operational costs, but also scalability, mobility and speedy research performance. The Hentsū mission is to help firms make the migration from traditional research tools to cloud-based grid computing.

Cloud Grid Computing is the future for research

  • Speedy research performance – Farming out large problems to be solved using parallel processing across many worker nodes or running multiple different jobs at once, speeds up research throughput.
  • Scalability –The elastic capacity of the cloud allows for the freedom to adjust your cloud grid computing resources based on immediate needs; scaling up or down as necessary. The dynamic nature of cloud infrastructure further permits an iterative evolution of the design or even very rapid changes as new research needs arise. This is a massive evolutionary step from the single researcher workstation we have been used to for many years.
  • Cost efficient – Unlike traditional research computing that may require upfront decisions on the technology and the purchasing of all the required machines before they can actually be used, cloud solutions eliminate the upfront cost of IT. Fast provisioning, flexible infrastructure and lower administration allow for lower cost of operations overall.
  • Mobility – Rather than being tied down to one location, your data and applications are available and accessible wherever you are and easily shared across multiple teams and offices.
Making quick changes to your strategies and backtesting against ever increasing market complexities present uphill battles. Grid computing alleviates unnecessary delays in job processing, creating faster output while allowing for quick adjustments to research strategies that might be failing.

Deploy your Cloud Grid Computing with Hentsū

We’ve built up a wealth of in-house expertise running grid computing workloads across all three major public cloud providers – Amazon AWS, Microsoft Azure and Google Compute Engine. We can get you up and running quickly with pre-tested designs and architectures, greatly eroding the traditional pains and TCO for running grid computing while helping you cut through technology choices and management of big data. Find out more about how grid computing can help maximize the efficiency of your research workloads at our upcoming New York event on January 25thhttps://hentsuprod.wpengine.com/events/infinitely-scalable-clusters/

Date/Time

Date(s) - 01/01/1970
12:00 AM - 12:00 AM

Location

600 5th ave. NY, NY