Únete a Open iT en IAITAM ACE 2026, el evento de referencia para los profesionales de la gestión de activos de TI que se enfrentan al complejo panorama actual de las auditorías. Descubre cómo las organizaciones están pasando de una defensa reactiva ante las auditorías a un cumplimiento normativo proactivo y basado en datos mediante análisis granulares de licencias.
Del 12 al 14 de mayo de 2026
El M Resort Spa y Casino
Las Vegas, Nevada
PATROCINADOR DE BRONCE
Tanto si quieres reducir el desperdicio, mejorar el cumplimiento normativo o maximizar el retorno de la inversión en tus inversiones en software, nuestro equipo está preparado para compartir contigo estrategias prácticas adaptadas a tu entorno. Acércate a nuestro stand en IAITAM y te mostraremos cómo puedes tomar el control total de tus activos de software y descubrir oportunidades de ahorro ocultas.
SESIÓN DE CONFERENCIAS
Las auditorías de software ya no son algo ocasional. Son frecuentes, complejas y tienen un impacto económico significativo.
En esta sesión, « Open iT » muestra cómo el análisis detallado de las licencias ayuda a los equipos de gestión de activos de TI (ITAM) a pasar de una defensa reactiva ante las auditorías a un control proactivo.
Aprende a:
Ponentes:
13 de mayo de 2026 | Miércoles
11:15 – 12:15
El M Resort Spa y Casino
Las Vegas, Nevada
¿Vas a asistir a IAITAM ACE 2026? Pongámonos en contacto antes de que todo se complique. Ponte en contacto con nuestro equipo antes del evento o envíanos un mensaje por LinkedIn para concertar una cita en Las Vegas. También puedes visitarnos en el stand n.º 42 durante la conferencia. Estaremos encantados de explicarte cómo el análisis detallado de las licencias puede ayudarte a reforzar el cumplimiento normativo, reducir el riesgo de auditoría y optimizar el gasto en software.
Por motivos de seguridad, resuelve este sencillo rompecabezas para confirmar que eres una persona real antes de enviar una contraseña de un solo uso (OTP).
Open iT
David Boyle
Dr. Dávid Felhős, Karman Mechanics
As engineering simulation becomes increasingly central to product development, organizations are facing growing pressure to scale computational workloads across shared on-premise and cloud-based environments. While advances in solver capability and compute infrastructure have expanded simulation capacity, resource availability is now frequently constrained by licensing and entitlement models that are tightly coupled to runtime behavior. In complex simulation workflows, unmanaged resource consumption can introduce variability in execution time, reduce throughput, and compromise the predictability of engineering schedules.
This presentation introduces a data-driven governance approach for managing simulation resource consumption as an integral part of the simulation process rather than an external administrative function. The framework treats licensing constraints as a system-level parameter, similar to compute availability or memory limits, and integrates consumption awareness directly into simulation workflow planning and execution. By correlating workload characteristics, such as concurrency, wall time, solver class, and execution context, with observed consumption patterns, the approach enables engineers and simulation managers to anticipate constraints before they impact critical project milestones.
The methodology is based on the collection and normalization of granular telemetry from execution environments and resource management layers. These data streams are aggregated into consumption profiles that describe how different classes of simulation workloads behave under varying operational conditions. Predictive models derived from historical execution data are then used to support proactive decision-making, including workload prioritization, queue management, and adaptive scheduling. Importantly, this governance layer operates independently of specific solvers or licensing technologies, ensuring portability across different simulation domains.
From a systems perspective, the presentation outlines an architecture that integrates data collection, analytics, and policy enforcement with existing simulation process infrastructure. Lightweight policy mechanisms are used to translate predictive insights into runtime controls, allowing organizations to balance competing objectives such as throughput, fairness, and schedule adherence. Particular emphasis is placed on maintaining engineer autonomy while introducing guardrails that prevent resource contention during peak demand periods.
Applied implementations of this framework demonstrate improved stability in simulation execution and reduced variability in job turnaround times. Rather than optimizing for cost alone, the analysis focuses on operational performance indicators that are directly relevant to engineering outcomes, including queue stability, utilization consistency, and predictability of simulation delivery. These improvements support more reliable design iteration cycles and reduce the risk of downstream delays in product development.
The session concludes by presenting a set of practical metrics and governance principles that can be adopted by organizations seeking to scale simulation workloads in a controlled and transparent manner. Attendees will gain insight into how data-driven governance can be embedded within simulation processes to support resilient, scalable, and well-coordinated engineering operations, particularly in environments where shared resources and complex workflows are the norm.