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Victor Lopez

Publications and source records attributed to Victor Lopez.

7 recordsLinked to original sources
arXiv2026

Hardware-Agnostic and Insightful Efficiency Metrics for Accelerated Systems: Definition and Implementation within TALP

The increasing adoption of heterogeneous platforms that combine CPUs with accelerators such as GPUs in high-performance computing (HPC) introduces new challenges for performance analysis and optimization. Traditional efficiency metrics, such as those proposed by the Performance Optimization and Productivity (POP) Center of Excellence, were designed primarily for homogeneous CPU-based systems and therefore, do not capture the complex interactions between host and device resources. In this work, we extend the POP efficiency framework to heterogeneous architectures by introducing a new hierarchy of metrics that separately evaluate host and device efficiency. On the host side, we quantify the effectiveness of hybrid execution and offloading operations. On the device side, we propose a multiplicative hierarchy analogous to the host hierarchy and define its Parallel Efficiency branch. Beyond their definition and formulation, we present the implementation of these metrics in the TALP module of the DLB library. TALP is a lightweight monitoring library that provides measurements both post mortem and at runtime, with outputs available in textual and machine-readable formats. We validate the proposed framework through synthetic benchmarks and three production HPC applications, demonstrating how the metrics expose inefficiencies in offloading, load balance, and orchestration. Results show that the extended TALP metrics provide actionable insights to guide developers in optimizing heterogeneous HPC codes.

cs.DC↗
arXiv2023

Runtime-Adaptable Selective Performance Instrumentation

Automated code instrumentation, i.e. the insertion of measurement hooks into a target application by the compiler, is an established technique for collecting reliable, fine-grained performance data. The set of functions to instrument has to be selected with care, as instrumenting every available function typically yields too large a runtime overhead, thus skewing the measurement. No "one-suits-all" selection mechanism exists, since the instrumentation decision is dependent on the measurement objective, the limit for tolerable runtime overhead and peculiarities of the target application. The Compiler-assisted Performance Instrumentation (CaPI) tool assists in creating such instrumentation configurations, by enabling the user to combine different selection mechanisms as part of a configurable selection pipeline, operating on a statically constructed whole-program call-graph. Previously, CaPI relied on a static instrumentation workflow which made the process of refining the initial selection quite cumbersome for large-scale codes, as the application had to be recompiled after each adjustment. In this work, we present new runtime-adaptable instrumentation capabilities for CaPI which do not require recompilation when instrumentation changes are made. To this end, the XRay instrumentation feature of the LLVM compiler was extended to support the instrumentation of shared dynamic objects. An XRay-compatible runtime system was added to CaPI that instruments selected functions at program start, thereby significantly reducing the required time for selection refinements. Furthermore, an interface to the TALP tool for recording parallel efficiency metrics was implemented, alongside a specialized selection module for creating suitable coarse-grained region instrumentations.

cs.PF↗
arXiv2021

Supercomputing Enabled Deployable Analytics for Disaster Response

First responders and other forward deployed essential workers can benefit from advanced analytics. Limited network access and software security requirements prevent the usage of standard cloud based microservice analytic platforms that are typically used in industry. One solution is to precompute a wide range of analytics as files that can be used with standard preinstalled software that does not require network access or additional software and can run on a wide range of legacy hardware. In response to the COVID-19 pandemic, this approach was tested for providing geo-spatial census data to allow quick analysis of demographic data for better responding to emergencies. These data were processed using the MIT SuperCloud to create several thousand Google Earth and Microsoft Excel files representative of many advanced analytics. The fast mapping of census data using Google Earth and Microsoft Excel has the potential to give emergency responders a powerful tool to improve emergency preparedness. Our approach displays relevant census data (total population, population under 15, population over 65, median age) per census block, sorted by county, through a Microsoft Excel spreadsheet (xlsx file) and Google Earth map (kml file). The spreadsheet interface includes features that allow users to convert between different longitude and latitude coordinate units. For the Google Earth files, a variety of absolute and relative colors maps of population density have been explored to provide an intuitive and meaningful interface. Using several hundred cores on the MIT SuperCloud, new analytics can be generated in a few minutes.

cs.DB↗
arXiv2019

The Engineering of Software-Defined Quantum Key Distribution Networks

Quantum computers will change the cryptographic panorama. A technology once believed to lay far away into the future is increasingly closer to real world applications. Quantum computers will break the algorithms used in our public key infrastructure and in our key exchange protocols, forcing a complete retooling of the cryptography as we know it. Quantum Key distribution is a physical layer technology immune to quantum or classical computational threats. However, it requires a physical substrate, and optical fiber has been the usual choice. Most of the time used just as a point to point link for the exclusive transport of the delicate quantum signals. Its integration in a real-world shared network has not been attempted so far. Here we show how the new programmable software network architectures, together with specially designed quantum systems can be used to produce a network that integrates classical and quantum communications, including management, in a single, production-level infrastructure. The network can also incorporate new quantum-safe algorithms and use the existing security protocols, thus bridging the gap between today's network security and the quantum-safe network of the future. This can be done in an evolutionary way, without zero-day migrations and the corresponding upfront costs. We also present how the technologies have been deployed in practice using a production network.

cs.NI↗
arXiv2018

Automatic Intent-Based Secure Service Creation Through a Multilayer SDN Network Orchestration

Growing traffic demands and increasing security awareness are driving the need for secure services. Current solutions require manual configuration and deployment based on the customer's requirements. In this work, we present an architecture for an automatic intent-based provisioning of a secure service in a multilayer - IP, Ethernet, and optical - network while choosing the appropriate encryption layer using an open-source software-defined networking (SDN) orchestrator. The approach is experimentally evaluated in a testbed with commercial equipment. Results indicate that the processing impact of secure channel creation on a controller is negligible. As the time for setting up services over WDM varies between technologies, it needs to be taken into account in the decision-making process.

cs.NI↗