https://store-images.s-microsoft.com/image/apps.20040.7f26ee8f-a7cd-4c37-834e-4653755dbe63.4c2f7eff-5601-4f6f-ad11-9a41abdab1ad.0cfb076c-e99d-4357-8978-13f4d5f5dc75
Wipro Nuage on Azure
par Wipro Ltd
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Wipro Nuage - Accelerating and Optimizing Silicon Design Workloads on Microsoft Azure
About Wipro Nuage Solution:
How it works for Semiconductor Industry customers?
Why Wipro?
Wipro Nuage is a smart
orchestrator powered by Artificial Intelligence and Machine Learning (AI/ML) that enables enterprises to
accelerate silicon design
workloads through the prediction
and optimization of resources
using cloud-native services. It is the only solution in the market that
addresses the business,
financial and technical
challenges the manufacturing semiconductor
industry faces when migrating
EDA workloads to Azure.
Key Capabilities:
Key Capabilities:
- AI/ML Enabled Solution - The AI/ML prediction engine ensures rightsized compute cores and memory. It further identifies and cost optimizes short-running workloads using preemptive instances
- Optimized HPC Costs - The solution lowers high performance computing (HPC) cost by sizing jobs and further eliminating idle compute times
- Self Service and Frictionless - The solution equips the users/engineers with self service capabilities for managing and governing tasks. It provides a dashboard for monitoring hosts, projects and license info. The solution also ensures a seamless integration and enables quick tool adoption.
How it works for Semiconductor Industry customers?
Electronic Design Automation (EDA) is a compute intensive process for any Semiconductor organization that requires a high-performance computing (HPC). While migrating to any cloud helps with
on-demand access to resources, costs can escalate
quickly if not managed properly. Customers will need an intelligent resource manager and predictor to
handle high compute and storage requirements for
spiky workloads and to optimize the license costs of
electronic design automation (EDA) tools.
Wipro's Nuage on Azure solution puts all this in reach by enabling businesses to minimize the HPC costs of EDA workloads, shift spending from CAPEX to OPEX, and improve asset utilization. With this solution, semiconductor companies can move away from fractured processes, experiences, and data sets to gain the benefits such as:
Wipro's Nuage on Azure solution puts all this in reach by enabling businesses to minimize the HPC costs of EDA workloads, shift spending from CAPEX to OPEX, and improve asset utilization. With this solution, semiconductor companies can move away from fractured processes, experiences, and data sets to gain the benefits such as:
- Ability to scale up and scale down infrastructure as demands change
- Move towards an almost zero wastage with right sized jobs
- Right instances, right sized jobs leads to shorter run times which leads to optimized license costs
Why Wipro?
Over 25 years of complete Silicon engineering lifecycle experience and Semi-conductor ecosystem partnerships for EDA
Differentiated Partnership with Microsoft with focused regional Go-to-Market
Strategic M&A Investments like Eximius, International TechneGroup Inc. (ITI) & Precision Automation And Robotics India Private Ltd. (PARI) to strengthen market leadership in Very Large Scale Integration (VLSI) and systems design services, Manufacturing and Industrial automation
- Strong Talent ecosystem with certified and experienced Cloud professionals. Wipro’s Microsoft Cloud business profile – $2.2B Cloud revenues, 80% YoY growth, 4 cloud studios, 50+ Delivery centers, 8000+ Microsoft Azure certified professionals.
Vue d’ensemble
https://store-images.s-microsoft.com/image/apps.21117.7f26ee8f-a7cd-4c37-834e-4653755dbe63.1749466d-7a7a-4c74-9c65-a946ab7d391a.237ba352-4be3-491b-9083-6e2c63fe6060
https://store-images.s-microsoft.com/image/apps.19825.7f26ee8f-a7cd-4c37-834e-4653755dbe63.1749466d-7a7a-4c74-9c65-a946ab7d391a.640aaf3c-346b-41e6-9f60-a25d4d8dc1e2
https://store-images.s-microsoft.com/image/apps.65252.7f26ee8f-a7cd-4c37-834e-4653755dbe63.1749466d-7a7a-4c74-9c65-a946ab7d391a.b71f18c7-1794-4a0f-b960-1aec0ebda9fd
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