Graphics processing unit (GPU), although a powerful performance-booster, also has many security vulnerabilities. Due to these, the GPU can act as a safe-haven for stealthy malware and the weakest 'link' in the security 'chain'. In this... more
Graphics processing unit (GPU), although a powerful performance-booster, also has many security vulnerabilities. Due to these, the GPU can act as a safe-haven for stealthy malware and the weakest 'link' in the security 'chain'. In this paper, we present a survey of techniques for analyzing and improving GPU security. We classify the works on key attributes to highlight their similarities and differences. More than informing users and researchers about GPU security techniques, this survey aims to increase their awareness about GPU security vulnerabilities and potential countermeasures.
This project designs an ARM System on Chip which displays a jagged Christmas tree using both, just the included processor of the system on a chip as well as a dedicated hardware accelerator module that accelerates the rasterisation of... more
This project designs an ARM System on Chip which displays a jagged Christmas tree using both, just the included processor of the system on a chip as well as a dedicated hardware accelerator module that accelerates the rasterisation of triangles. This is displayed on a 640x480 VGA screen connected to an Intel DE-1 FPGA
Fuzzy Logic System (FLS) is an efficient method to solve engineering problems. However, the training of a Fuzzy Logic System is a time-consuming task. Optimization Algorithm can be used to optimize the rule base of any FLS. Out of Type-1... more
Fuzzy Logic System (FLS) is an efficient method to solve engineering problems. However, the training of a Fuzzy Logic System is a time-consuming task. Optimization Algorithm can be used to optimize the rule base of any FLS. Out of Type-1 FLS and Type-2 FLS, the type-2 found to be more effective to deal with noisy data. Due to their computational requirements Interval Type-2 (IT2) has been preferred over General Type-2. Whale Optimization Algorithm (WOA)has been introduced recently. The algorithm has been tested on different engineering problems and is found to be more effective. General Purpose Computing using graphics Processing Unit (GPGPU) is a new way to solve compute intensive problems on Graphics Processing Unit (GPU). CUDA-C is a parallel language that can be used to execute parallel code NVIDIA GPU. This paper integrates IT2 FLS, WOA and Processing Power of GPU. A toolbox is proposed that can be used to optimize the rule base in parallel. The toolbox provides both the implementations, i.e. serial and Parallel. FLS WOA Toolbox is design in such a way that user can pass parameter dynamically according to their need without interfacing with the code.
Due to their high density and near-zero leakage power consumption, non-volatile memories (NVMs) are promising candidates for designing future memory systems. However, compared to conventional memories, NVMs also face more-severe security... more
Due to their high density and near-zero leakage power consumption, non-volatile memories (NVMs) are promising candidates for designing future memory systems. However, compared to conventional memories, NVMs also face more-severe security threats, e.g., the limited write endurance of NVMs makes them vulnerable to write-attacks. Also, the non-volatility of NVMs allows the data to persist even after power-off, which can be accessed by a malicious agent. Further, encryption endangers NVM lifetime and performance by reducing the efficacy of redundant-write avoidance techniques. In this paper, we present a survey of techniques for improving security of NVM-based memories by addressing the aforementioned challenges. We highlight the key ideas of the techniques along with their similarities and differences. This paper is expected to be useful for researchers and practitioners in the area of memory and system security.
Due to their high density and near-zero leakage power consumption, non-volatile memories (NVMs) are promising candidates for designing future memory systems. However, compared to conventional memories, NVMs also face more-severe security... more
Due to their high density and near-zero leakage power consumption, non-volatile memories (NVMs) are promising candidates for designing future memory systems. However, compared to conventional memories, NVMs also face more-severe security threats, e.g., the limited write endurance of NVMs makes them vulnerable to write-attacks. Also, the non-volatility of NVMs allows the data to persist even after power-off, which can be accessed by a malicious agent. Further, encryption endangers NVM lifetime and performance by reducing the efficacy of redundant-write avoidance techniques. In this paper, we present a survey of techniques for improving security of NVM-based memories by addressing the aforementioned challenges. We highlight the key ideas of the techniques along with their similarities and differences. This paper is expected to be useful for researchers and practitioners in the area of memory and system security.
Computational neuroscience is being revolutionized with the advent of multi-electrode arrays that provide real-time, dynamic, perspectives into brain function. Mining event streams from these chips is critical to understanding the firing... more
Computational neuroscience is being revolutionized with the advent of multi-electrode arrays that provide real-time, dynamic, perspectives into brain function. Mining event streams from these chips is critical to understanding the firing patterns of neurons and to gaining insight into the underlying cellular activity. We present a GPGPU solution to mining spike trains. We focus on mining frequent episodes which captures coordinated events across time even in the presence of intervening background/“junk ” events. Our algorithmic contributions are two-fold: MapConcatenate, a new computationto-core mapping scheme, and a two-pass elimination approach to quickly find supported episodes from a large number of candidates. Together, they help realize a real-time “chip-on-chip ” solution to neuroscience data mining, where one chip (the multi-electrode array) supplies the spike train data and another (the GPGPU) mines it at a scale unachievable previously. Evaluation on both synthetic and rea...
Due to their high density and near-zero leakage power consumption, non-volatile memories (NVMs) are promising candidates for designing future memory systems. However, compared to conventional memories, NVMs also face more-severe security... more
Due to their high density and near-zero leakage power consumption, non-volatile memories (NVMs) are promising candidates for designing future memory systems. However, compared to conventional memories, NVMs also face more-severe security threats, e.g., the limited write endurance of NVMs makes them vulnerable to write-attacks. Also, the non-volatility of NVMs allows the data to persist even after power-off, which can be accessed by a malicious agent. Further, encryption endangers NVM lifetime and performance by reducing the efficacy of redundant-write avoidance techniques. In this paper, we present a survey of techniques for improving security of NVM-based memories by addressing the aforementioned challenges. We highlight the key ideas of the techniques along with their similarities and differences. This paper is expected to be useful for researchers and practitioners in the area of memory and system security.
