New hardware support transactional memory and parallel debugging in multicore processors

This thesis contributes to the area of hardware support for parallel programming by introducing new hardware elements in multicore processors, with the aim of improving the performance and optimize new tools, abstractions and applications related with parallel programming, such as transactional memory and data race detectors. Specifically, we configure a hardware transactional memory system with signatures as part of the hardware support, and we develop a new hardware filter for reducing the signature size. We also develop the first hardware asymmetric data race detector (which is also able to tolerate them), based also in hardware signatures. Finally, we propose a new module of hardware signatures that solves some of the problems that we found in the previous tools related with the lack of flexibility in hardware signatures

DAMOV: A New Methodology and Benchmark Suite for Evaluating Data Movement Bottlenecks

Data movement between the CPU and main memory is a first-order obstacle against improving performance, scalability, and energy efficiency in modern systems. Computer systems employ a range of techniques to reduce overheads tied to data movement, spanning from traditional mechanisms (e.g., deep multi-level cache hierarchies, aggressive hardware prefetchers) to emerging techniques such as Near-Data Processing (NDP), where some computation is moved close to memory. Our goal is to methodically identify potential sources of data movement over a broad set of applications and to comprehensively compare traditional compute-centric data movement mitigation techniques to more memory-centric techniques, thereby developing a rigorous understanding of the best techniques to mitigate each source of data movement. With this goal in mind, we perform the first large-scale characterization of a wide variety of applications, across a wide range of application domains, to identify fundamental program properties that lead to data movement to/from main memory. We develop the first systematic methodology to classify applications based on the sources contributing to data movement bottlenecks. From our large-scale characterization of 77K functions across 345 applications, we select 144 functions to form the first open-source benchmark suite (DAMOV) for main memory data movement studies. We select a diverse range of functions that (1) represent different types of data movement bottlenecks, and (2) come from a wide range of application domains. Using NDP as a case study, we identify new insights about the different data movement bottlenecks and use these insights to determine the most suitable data movement mitigation mechanism for a particular application. We open-source DAMOV and the complete source code for our new characterization methodology at https://github.com/CMU-SAFARI/DAMOV.Comment: Our open source software is available at https://github.com/CMU-SAFARI/DAMO

Transparency on YouTube for radon risk communication

Introducción: La evidencia científica ha demostrado la relación entre la exposición al radón en entornos interiores y el cáncer de pulmón. Por esta razón, el gas radón se considera una amenaza para la salud pública. Además, se ha confirmado que YouTube es una fuente de información médica. Metodología: Esta investigación examina YouTube como un medio para la difusión global de información sobre el radón. Se identifican todos los canales que contienen videos sobre este gas, junto con las áreas geográficas en las que operan, el idioma que utilizan para transmitir, el número de suscriptores y la cantidad de visualizaciones que acumulan. Utilizando una muestra de canales específicamente centrados en el radón, se examina la presencia de este tema en YouTube mediante un modelo metodológico que explora temas, narrativas y estrategias de difusión. Resultados: Los resultados revelan la ausencia de cámaras de eco y la falta de conciencia en esta red social con respecto a los problemas de salud pública relacionados con el gas radón. Discusión y Conclusiones: El estudio destaca la presencia limitada de vídeos relacionados con el radón en YouTube, con una predominancia de contenido en inglés, que restringe la accesibilidad en regiones no anglófonas. Los canales sobre el radón infrautilizan las funciones de YouTube y carecen de participación de la comunidad, revelando una brecha significativa en el reconocimiento del radón como un problema de salud pública en la plataforma. Aunque algunos canales exitosos demuestran buenas prácticas, la conciencia general sigue siendo insuficiente.Radon in Spain: Perception of public opinion, media agenda and risk communication (RAPAC). Nuclear Safety Council (Consejo de Seguridad Nuclear) (SUBV-13/2021).S

DRAM Bender: An Extensible and Versatile FPGA-based Infrastructure to Easily Test State-of-the-art DRAM Chips

To understand and improve DRAM performance, reliability, security and energy efficiency, prior works study characteristics of commodity DRAM chips. Unfortunately, state-of-the-art open source infrastructures capable of conducting such studies are obsolete, poorly supported, or difficult to use, or their inflexibility limit the types of studies they can conduct. We propose DRAM Bender, a new FPGA-based infrastructure that enables experimental studies on state-of-the-art DRAM chips. DRAM Bender offers three key features at the same time. First, DRAM Bender enables directly interfacing with a DRAM chip through its low-level interface. This allows users to issue DRAM commands in arbitrary order and with finer-grained time intervals compared to other open source infrastructures. Second, DRAM Bender exposes easy-to-use C++ and Python programming interfaces, allowing users to quickly and easily develop different types of DRAM experiments. Third, DRAM Bender is easily extensible. The modular design of DRAM Bender allows extending it to (i) support existing and emerging DRAM interfaces, and (ii) run on new commercial or custom FPGA boards with little effort. To demonstrate that DRAM Bender is a versatile infrastructure, we conduct three case studies, two of which lead to new observations about the DRAM RowHammer vulnerability. In particular, we show that data patterns supported by DRAM Bender uncovers a larger set of bit-flips on a victim row compared to the data patterns commonly used by prior work. We demonstrate the extensibility of DRAM Bender by implementing it on five different FPGAs with DDR4 and DDR3 support. DRAM Bender is freely and openly available at https://github.com/CMU-SAFARI/DRAM-Bender.Comment: To appear in TCAD 202

SpyHammer: Using RowHammer to Remotely Spy on Temperature

RowHammer is a DRAM vulnerability that can cause bit errors in a victim DRAM row by just accessing its neighboring DRAM rows at a high-enough rate. Recent studies demonstrate that new DRAM devices are becoming increasingly more vulnerable to RowHammer, and many works demonstrate system-level attacks for privilege escalation or information leakage. In this work, we leverage two key observations about RowHammer characteristics to spy on DRAM temperature: 1) RowHammer-induced bit error rate consistently increases (or decreases) as the temperature increases, and 2) some DRAM cells that are vulnerable to RowHammer cause bit errors only at a particular temperature. Based on these observations, we propose a new RowHammer attack, called SpyHammer, that spies on the temperature of critical systems such as industrial production lines, vehicles, and medical systems. SpyHammer is the first practical attack that can spy on DRAM temperature. SpyHammer can spy on absolute temperature with an error of less than 2.5 {\deg}C at the 90th percentile of tested temperature points, for 12 real DRAM modules from 4 main manufacturers