Hammerspace and Parallel Works Revolutionize Hybrid Cloud Solutions
Introducing a Unified Solution for Data Management
Hammerspace and Parallel Works are set to transform the landscape of hybrid and multi-cloud environments with their unique solution for compute and data orchestration. This collaboration enables IT infrastructure teams, AI teams, and research computing teams to efficiently orchestrate compute, storage, and data workloads across multiple sites and clouds. This innovation offers organizations the ability to scale their cloud resources on-demand, making it an essential tool for modern computing needs.
The Vision Behind the Partnership
According to David Flynn, the Founder and CEO of Hammerspace, the necessity for innovators to execute complete workloads across various compute clusters has never been more critical. The flexibility to switch between CPUs for data preparation and GPUs for processing enhances resource management significantly. Flynn emphasizes that their partnership with Parallel Works is a game-changer, allowing seamless orchestration across compute and data which accelerates innovation and minimizes latency.
A New Era of Resource Management
Matthew Shaxted, the CEO of Parallel Works, echoes this sentiment by highlighting the significant advancement this partnership brings to the management of compute resources and data. By combining their expertise in high-performance computing (HPC) and AI workload orchestration with Hammerspace's capabilities in parallel file systems, they are paving the way for better application portability and dynamic task placement. This empowering approach aids organizations in optimizing their resources effectively, enhancing performance and simplifying hybrid infrastructure management.
Addressing the Challenge of Distributed Workloads
AI and HPC workloads necessitate considerable compute resources alongside low-latency access to large datasets. However, data and compute resources are frequently scattered across various locations, complicating efficient data processing. Hammerspace and Parallel Works have co-developed a solution that automates the provisioning and management of both local and cloud compute resources, simplifying the flow of data across these resources.
Harnessing Powerful Automation
At the heart of their solution, Parallel Works' ACTIVATE functions as a unified control plane. This system streamlines the creation, provisioning, and management of compute resources across multiple data centers and cloud environments. Additionally, it automates workflows, including the management of job scheduling through Slurm instances tailored for HPC environments.
Revolutionizing Data Storage
Serving as the data platform, Hammerspace provides high-performance file and object storage solutions. The platform offers a Global Namespace that connects sites and clouds while automating data flow within that namespace using its Data Orchestration services. This ensures that data is delivered to HPC servers, regardless of their location, and allows for detailed orchestration policy settings that can be applied to shares, directories, and individual files.
Cost Efficiency and Resource Optimization
The integrated solution delivers value by enabling administrators to create and manage storage clusters effectively from the Parallel Works ACTIVE Control Plane console. A notable advantage of this approach is its ability to utilize elastic cloud resources for burst computing capacity. Companies can now optimize their infrastructure while benefiting from the simplicity of a fully managed cloud service, all while reducing costs compared to traditional cloud infrastructure services. This is particularly essential in today's economic environment where minimizing expenses is crucial for operational sustainability.
Engagement and Learning Opportunities
This pioneering technology will be discussed further in an engaging webinar scheduled by the organizations. David Flynn and Matthew Shaxted will explore the future of hybrid and multi-cloud orchestration. They aim to offer valuable insights into how their unified solution can enhance data management and streamline workloads within the HPC and AI landscape.
About Hammerspace
Hammerspace is reimagining the management and utilization of unstructured data. Their Global Data Platform unifies unstructured data across edges, data centers, and clouds, providing unparalleled performance for AI and data analytics. By orchestrating data storage across various locations, Hammerspace eliminates data silos and ensures access to crucial data resources.
About Parallel Works
Parallel Works' ACTIVATE serves as an advanced control plane for HPC and AI resource management, enhancing productivity through intuitive interfaces and API-driven processes. This empowers teams to manage and provision compute resources effectively, fostering collaboration and innovation in research.
Frequently Asked Questions
What is the main goal of the Hammerspace and Parallel Works partnership?
The partnership aims to provide a unified solution for compute and data orchestration across hybrid and multi-cloud environments, optimizing resource management and facilitating better performance.
How does the ACTIVATE control plane work?
ACTIVATE streamlines creating, provisioning, and managing compute resources across multiple environments while automating workflows and job scheduling operations.
Why is low-latency access important for AI and HPC workloads?
Low-latency access is vital because many AI and HPC applications require immediate data processing, which can be hindered by delays in accessing data stored across various locations.
What are the benefits of the Hammerspace platform?
Hammerspace provides high-performance data storage solutions, a Global Namespace for seamless data flow, and tools to set detailed orchestration policies, enhancing data accessibility and management.
Where can I learn more about this unified solution?
Further exploration of this unified solution will be presented in a scheduled webinar where experts from both companies discuss the practical implications and benefits.
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