A survey of emerging architectural techniques for improving cache energy consumption

The search goes on for another ground breaking phenomenon to reduce the ever-increasing disparity between the CPU performance and storage. There are encouraging breakthroughs in enhancing CPU performance through fabrication technologies and changes in chip designs but not as much luck has been struck with regards to the computer storage resulting in material negative system performance. A lot of research effort has been put on finding techniques that can improve the energy efficiency of cache architectures. This work is a survey of energy saving techniques which are grouped on whether they save the dynamic energy, leakage energy or both. Needless to mention, the aim of this work is to compile a quick reference guide of energy saving techniques from 2013 to 2016 for engineers, researchers and students

Performance and Memory Space Optimizations for Embedded Systems

Embedded systems have three common principles: real-time performance, low power consumption, and low price (limited hardware). Embedded computers use chip multiprocessors (CMPs) to meet these expectations. However, one of the major problems is lack of efficient software support for CMPs; in particular, automated code parallelizers are needed. The aim of this study is to explore various ways to increase performance, as well as reducing resource usage and energy consumption for embedded systems. We use code restructuring, loop scheduling, data transformation, code and data placement, and scratch-pad memory (SPM) management as our tools in different embedded system scenarios. The majority of our work is focused on loop scheduling. Main contributions of our work are: We propose a memory saving strategy that exploits the value locality in array data by storing arrays in a compressed form. Based on the compressed forms of the input arrays, our approach automatically determines the compressed forms of the output arrays and also automatically restructures the code. We propose and evaluate a compiler-directed code scheduling scheme, which considers both parallelism and data locality. It analyzes the code using a locality parallelism graph representation, and assigns the nodes of this graph to processors.We also introduce an Integer Linear Programming based formulation of the scheduling problem. We propose a compiler-based SPM conscious loop scheduling strategy for array/loop based embedded applications. The method is to distribute loop iterations across parallel processors in an SPM-conscious manner. The compiler identifies potential SPM hits and misses, and distributes loop iterations such that the processors have close execution times. We present an SPM management technique using Markov chain based data access. We propose a compiler directed integrated code and data placement scheme for 2-D mesh based CMP architectures. Using a Code-Data Affinity Graph (CDAG) to represent the relationship between loop iterations and array data, it assigns the sets of loop iterations to processing cores and sets of data blocks to on-chip memories. We present a memory bank aware dynamic loop scheduling scheme for array intensive applications.The goal is to minimize the number of memory banks needed for executing the group of loop iterations

Smart card security

Smart Card devices are commonly used on many secure applications where there is a need to identify the card holder in order to provide a personalised service. The value of access to locked data and services makes Smart Cards a desirable attack target for hackers of all sorts. The range of attacks a Smart Card and its environment can be subjected to ranges from social engineering to exploiting hardware and software bugs and features. This research has focused on several hardware related attacks and potential threats. Namely, power glitch attack, power analysis, laser attack, the potential effect on security of memory power consumption reduction techniques and using a re-configurable instruction set as method to harden opcode interpretation. A semi-automated simulation environment to test designs against glitch attacks and power analysis has been developed. This simulation environment can be easily integrated within Atmel’s design flow to bring assurance of their designs’ behaviour and permeability to such attacks at an early development stage. Previous power analysis simulation work focused on testing the implementation of part of the cryptographic algorithm. This work focuses on targeting the whole algorithm, allowing the test of a wider range of countermeasures. A common glitch detection approach is monitoring the power supply for abnormal voltage values and fluctuations. This approach can fail to detect some fast glitches. The alternative approach used in this research monitors the effects of a glitch on a mono-stable circuit sensitive to fault injection by glitch attacks. This work has resulted in a patented glitch detector that improves the overall glitch detection range. The use of radiation countermeasures as laser countermeasures and potential sensors has been investigated too. Radiation and laser attacks have similar effects on silicon devices. Whilst several countermeasures against radiation have been developed over the years, almost no explicit mention of laser countermeasures was found. This research has demonstrated the suitability of using some radiation countermeasures as laser countermeasures. Memory partitioning is a static and dynamic power consumption reduction technique successfully used in various devices. The nature of Smart Card devices restricts the applicability of some aspects of this power reduction technique. This research line has resulted in the proposal of a memory partitioning approach suitable to Smart Cards