CPU caches have become an essential component in many computer systems as they can significantly increase system performance by alleviating the effects of memory latency. For many designers part of the system design flow is the selection of an appropriately configured cache, a task which can be performed using cache simulators. Exploring the entire design space through precise cache simulation is a lengthy process, and while certain cache replacement policies have been optimised for fast simulation execution (such as LRU and FIFO), no effective optimisations have been proposed for an extremely effective replacement policy: Pseudo Least Recently Used tree-based, also known as PLRUt. In this paper we are the first to present a number of characteristics of the PLRUt replacement policy that lend themselves to the design of an optimised hash table-based cache simulator. We demonstrate that our optimised simulator is up to 1.93x faster than an un-optimised implementation.

Judicious selection of cache configuration is critical in embedded systems as the cache design can impact power consumption and processor throughput. A large cache increases cache hits but requires more hardware and more power, and will be slower for each access. A smaller cache is more economical and faster per access, but may result in significantly more cache misses resulting in a slower system. For a given application or a class of applications on a given hardware system, the designer can aim to optimise cache configuration through cache simulation. We present here the first multiple cache simulator based on hardware. The FPGA implementation is characterised by a trace consumption rate of 100MHz making our cache simulation core up to 53x faster, for a set of benchmarks, than the fastest software based cache simulator. Our cache simulator can determine the hit rates of 308 cache configurations, of which it can determine the hit rates of 44 simultaneously.

Cache memories have become an essential component in modern processors. To find the cache configuration that best fits the targeted power, timing and cost criteria of the system, designers conventionally run a lengthy cache simulation in software. In this paper we present MASH{fifo}, the first Multiple cAche Simulator in Hardware (MASH) supporting the FIFO replacement policy. We measured a speedup of up to 11x when compared to the fastest software alternative, CIPARSim. We also investigate an in-system implementation where multiple cache simulation is performed in real time from within an embedded system.

Multi-level caches are widely used to improve the memory access speed of multiprocessor systems. Deciding on a suitable set of cache memories for an application specific embedded system's memory hierarchy is a tedious problem, particularly in the case of MPSoCs. To accurately determine the number of hits and misses for all the configurations in the design space of an MPSoC, researchers extract the trace first using Instruction set simulators and then simulate using a software simulator. Such simulations take several hours to months. We propose a novel method based on specialized hardware which can quickly simulate the design space of cache configurations for a shared memory multiprocessor system on an FPGA, by analyzing the memory traces and calculating the cache hits and misses simultaneously. We demonstrate that our simulator can explore the cache design space of a quad-core system with private L1caches and a shared L2cache, over a range of standard benchmarks, taking as less as 0.106 seconds per million memory accesses, which is up to 456 times faster than the fastest known software based simulator. Since we emulate the program and analyze memory traces simultaneously, we eliminate the need to extract multiple memory access traces prior to simulation, which saves a significant amount of time during the design stage.

JPEG Encoding is a commonly performed application that is also very process and memory intensive, and not suited for low-power embedded systems with narrow data buses and small amounts of memory. An embedded system may also need to adapt its application in order to meet varying system constraints such as power, energy, time or bandwidth. We present here an extremely compact JPEG encoder that uses very few system resources, and which is capable of dynamically changing its Quality of Service (QoS) on the fly. The application was tested on a NIOS II core, AVR, and PIC24 microcontrollers with excellent results.

The rapid push towards the minimization of the feature sizes of the process technology nodes in the nano-CMOS era has significantly increased the power densities and made State-of-the-Art FPGAs vulnerable to diverse problems induced by excessive temperatures. As a result, there is a prominent need to accurately study the FPGA thermal characteristics. Our experimental setup employs a thermal camera that captures the infrared emissions from the silicon wafer of an FPGA die allowing us to evaluate the accuracy of the methods conventionally used for thermal analysis, such as thermal simulations. Based on our observation that the memory interface is the thermal hotspot of an FPGA-based embedded system, we demonstrate that the cache plays a dominant thermal role by reducing memory accesses; we carefully examine the influence of various cache parameters on the FPGA temperature and propose a model linking these quantities, with an average maximum error of only 0.64°C.