La jerarquía de caches y la red en el chip (NoC) son dos componentes clave de los chip multiprocesadores (CMPs). La mayoría del trafico en la NoC se debe a mensajes que las caches envían según lo que establece el protocolo de coherencia. La cantidad de trafico, el porcentaje de mensajes cortos y largos y el patrón de trafico en general varían dependiendo de la geometría de las caches y del protocolo de coherencia. La arquitectura de la NoC y la jerarquía de caches están de hecho firmemente acopladas, y estos dos componentes deben ser diseñados y evaluados conjuntamente para estudiar como el variar uno afecta a las prestaciones del otro. Además, cada componente debe ajustarse a los requisitos y a las oportunidades del otro, y al revés. Normalmente diferentes clases de mensajes se envían por diferentes redes virtuales o por NoCs con diferente ancho de banda, separando mensajes largos y cortos. Sin embargo, otra clasificación de los mensajes se puede hacer dependiendo del tipo de información que proveen: algunos mensajes, como las peticiones de datos, necesitan campos para almacenar información (dirección del bloque, tipo de petición, etc.); otros, como los mensajes de reconocimiento (ACK), no proporcionan ninguna información excepto por el ID del nodo destino: solo proveen una información de tipo temporal, en el sentido que la recepción de un ACK indica que el nodo fuente ha recibido el mensaje al que está contestando con el ACK y completado todas las operaciones determinadas por el protocolo de coherencia. Esta segunda clase de mensaje no necesita de mucho ancho de banda: la latencia es mucho mas importante, dado que el nodo destino esta típicamente bloqueado esperando la recepción de ellos. En este trabajo de tesis se desarrolla una red dedicada para trasmitir la segunda clase de mensajes; la red es muy sencilla y rápida, y permite la entrega de los ACKs con una latencia de pocos ciclos de reloj. Reduciendo la latencia y el trafico en la NoC debido a los ACKs, es posible: -acelerar la fase de invalidación en fase de escritura en un sistema que usa un protocolo de coherencia basado en directorios -mejorar las prestaciones de un protocolo de coerencia basado en broadcast, hasta llegar a prestaciones comparables con las de un protocolo de directorios pero sin el coste de área debido a la necesidad de almacenar el directorio -implementar un mapeado dinámico de bloques a las caches de ultimo nivel de forma eficiente, con el objetivo de acercar cuanto al máximo los bloques a los cores que los utilizan El objetivo final es obtener un co-diseño de NoC y jerarquía de caches que minimice los problemas de escalabilidad de los protocolos de coherencia. Como gran objetivo final, se pretende la implementación de un CMP con ubicación dinámica de los recursos de cache y red, tal que estos recursos se puedan particionar de forma eficiente e independiente para asignar diferentes particiones a diferentes aplicaciones en un entorno virtualizado. / Lodde, M. (2014). Smart Memory and Network-On-Chip Design for High-Performance Shared-Memory Chip Multiprocessors [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/35325 / TESIS

Mechanisms for improving the execution efficiency of graph algorithms on Data-Parallel Architectures were proposed and identified. Execution of graph algorithms on GPGPU architectures, the prevalent data-parallel architectures was considered. Irregular and data dependent accesses in graph algorithms were found to cause significant idle cycles in GPGPU cores. A prefetching mechanism that reduced the amount of idle cycles by prefetching a data-dependent access pattern found in graph algorithms was proposed. Storing prefetches in unused spare registers in addition to storing them in the cache was shown to be more effective by the prefetching mechanism. The design of the cache hierarchy for graph algorithms was explored. First, an exclusive cache hierarchy was shown to be beneficial at the cost of increased traffic; a region based exclusive cache hierarchy was shown to be similar in performance to an exclusive cache hierarchy while reducing on-chip traffic. Second, bypassing cache blocks at both the level one and level two caches was shown to be beneficial. Third, the use of fine-grained memory accesses (or cache sub-blocking) was shown to be beneficial. The combination of cache bypassing and fine-grained memory accesses was shown to be more beneficial than applying the two mechanisms individually. Finally, the impact of different implementation strategies on algorithm performance was evaluated for the breadth first search algorithm using different input graphs and heuristics to identify the best performing implementation for a given input graph were also discussed.

Pervasive use of GPUs across multiple disciplines is a result of continuous adaptation of the GPU architectures to address the needs of upcoming application domains. One such vital improvement is the introduction of the on-chip cache hierarchy, used primarily to filter the high bandwidth demand to the off-chip memory. However, in contrast to traditional CPUs, the cache hierarchy in GPUs is presented with significantly different challenges such as cache thrashing and bandwidth bottlenecks, arising due to small caches and high levels of memory traffic. These challenges lead to severe congestion across the memory hierarchy, resulting in high memory access latencies. In memory-intensive applications, such high memory access latencies often get exposed and can no longer be hidden through multithreading, and therefore adversely impact system performance. In this thesis, we address the inefficiencies across the memory hierarchy in GPUs that lead to such high levels of congestion. We identify three major factors contributing to poor memory system performance: first, disproportionate and insufficient bandwidth resources in the cache hierarchy; second, poor cache management policies; and third, high levels of multithreading. In order to revitalize the memory hierarchy by addressing the above limitations, we propose a three-pronged approach. First, we characterize the bandwidth bottlenecks present across the memory hierarchy in GPUs and identify the architectural parameters that are most critical in alleviating congestion. Subsequently, we explore the architectural design space to mitigate the bandwidth bottlenecks in a cost-effective manner. Second, we identify significant inter-core reuse in GPUs, presenting an opportunity to reuse data among the L1s. We exploit this reuse by connecting the L1 caches with a lightweight ring network to facilitate inter-core communication of shared data. We show that this technique reduces traffic to the L2 cache, freeing up the bandwidth for other accesses. Third, we present Poise, a machine learning approach to mitigate cache thrashing and bandwidth bottlenecks by altering the levels of multi-threading. Poise comprises a supervised learning model that is trained offline on a set of profiled kernels to make good warp scheduling decisions. Subsequently, a hardware inference engine is used to predict good warp scheduling decisions at runtime using the model learned during training. In summary, we address the problem of bandwidth bottlenecks across the memory hierarchy in GPUs by exploring how to best scale, supplement and utilize the existing bandwidth resources. These techniques provide an effective and comprehensive methodology to mitigate the bandwidth bottlenecks in the GPU memory hierarchy.

SIMLOX is a discrete-event simulation software developed by Systecon AB for analysing logistic support solution scenarios. To cope with ever larger problems, SIMLOX's simulation engine was recently enhanced with a parallel execution mechanism in order to take advantage of multi-core processors. However, this extension did not result in the desired reduction in runtime for all simulation scenarios even though the parallelisation strategy applied had promised linear speedup. Therefore, an in-depth analysis of the limiting scalability bottlenecks became necessary and has been carried out in this project. Through the use of a low-overhead profiler and microarchitecture analysis, the root causes were identified: atomic operations causing a high communication overhead, poor locality leading to translation lookaside buffer thrashing, and hot spots that consume significant amounts of CPU time. Subsequently, appropriate optimisations to overcome the limiting factors were implemented: eliminating the expensive operations, more efficient handling of heap memory through the use of a scalable memory allocator, and data structures that make better use of caches. Experimental evaluation using real world test cases demonstrated a speedup of at least 6.75x on an eight-core processor. Most cases even achieve a speedup of more than 7.2x. The various optimisations implemented further helped to lower run times for sequential execution by 1.5x or more. It can be concluded that achieving nearly linear speedup on a multi-core processor is possible in practice for discrete-event simulation. / SIMLOX är en kommersiell mjukvara utvecklad av Systecon AB, vars huvudsakliga funktion är en händelsestyrd simuleringskärna för analys av underhållslösningar för komplexa tekniska system. För hantering av stora problem så används parallellexekvering för simuleringen, vilket i teorin borde ge en nästan linjär skalning med antal trådar. Prestandaförbättringen som observerats i praktiken var dock ytterst begränsad, varför en ordentlig analys av skalbarheten har gjorts i detta projekt. Genom användandet av ett profileringsverktyg med liten overhead och mikroarkitektur-analys, så kunde orsakerna hittas: atomiska operationer som skapar mycket overhead för kommunikation, dålig lokalitet ger fragmentering vid översättning till fysiska adresser och dåligt utnyttjande av TLB-cachen, och vissa flaskhalsar som kräver mycket CPU-kraft. Därefter implementerades och testade optimeringar för att undvika de identifierade problem. Testade lösningar inkluderar eliminering av dyra operationer, ökad effektivitet i minneshantering genom skalbara minneshanteringsalgoritmer och implementation av datastrukturer som ger bättre lokalitet och därmed bättre användande av cache-strukturen. Verifiering på verkliga testfall visade på uppsnabbningar på åtminstone 6.75 gånger på en processor med 8 kärnor. De flesta fall visade på en uppsnabbning med en faktor större än 7.2. Optimeringarna gav även en uppsnabbning med en faktor på åtminstone 1.5 vid sekventiell exekvering i en tråd. Slutsatsen är därmed att det är möjligt att uppnå nästan linjär skalning med antalet kärnor för denna typ av händelsestyrd simulering.