Priority Based Switch Allocator in Adaptive Physical Channel Regulator for On Chip Interconnects

Chip multiprocessors (CMPs) are now popular design paradigm for microprocessors due to their power, performance and complexity advantages where a number of relatively simple cores are integrated on a single die. On chip interconnection network (NoC) is an excellent architectural paradigm which offers a stable and generalized communication platform for large scale of chip multiprocessors. The existing model APCR has three regulation schemes designed at switch allocation stage of NoC router pipelining, such as monopolizing, fair-sharing and channel-stealing. Its aim is to fairly allocate physical bandwidth in the form of flit level transmission unit while breaking the conventional assumptions i.e.its size is same as phit size. They have implemented channel-stealing scheme using the existing round-robin scheduler which is a well known scheduling algorithm for providing fairness, which is not an optimal solution. In this thesis, we have extended the efficiency of APCR model and propose three efficient scheduling policies for the channel stealing scheme in order to provide better quality of service (QoS). Our work can be divided into three parts. In the first part, we implemented ratio based scheduling technique in which we keep track of average number of its sent from each input in every cycle. It not only provides fairness among virtual channels (VCs), but also increases the saturation throughput of the network. In the second part, we have implemented an age based scheduling technique where we prioritize the VC, based on the age of the requesting flits. The age of each request is calculated as the difference between the time of injection and the current simulation time. Age based scheduler minimizes the packet latency. In the last part, we implemented a Static-Priority based scheduler. In this case, we arbitrarily assign random priorities to the packets at the time of their injection into the network. In this case, the high priority packets can be forwarded to any of the VCs, whereas the low priority packets can be forwarded to a limited number of VCs. So, basically Static-Priority based scheduler limits the accessibility on the number of VCs depending upon the packet priority. We study the performance metrics such as the average packet latency, and saturation throughput resulted by all the three new scheduling techniques. We demonstrate our simulation results for all three scheduling policies i.e. bit complement, transpose and uniform random considering from very low (no load) to high load injection rates. We evaluate the performance improvement because of our proposed scheduling techniques in APCR comparing with the performance of basic NoC design. The performance is also compared with the results found in monopolizing, fair-sharing and round-robin schemes for channel-stealing of APCR. It is observed from the simulation results using our detailed cycle-accurate simulator that our new scheduling policies implemented in APCR model improves the network throughput by 10% in case of synthetic workloads, compared with the existing round-robin scheme. Also, our scheduling policy in APCR model outperforms the baseline router by 28X under synthetic workloads

Optimized Surface Code Communication in Superconducting Quantum Computers

Quantum computing (QC) is at the cusp of a revolution. Machines with 100 quantum bits (qubits) are anticipated to be operational by 2020 [googlemachine,gambetta2015building], and several-hundred-qubit machines are around the corner. Machines of this scale have the capacity to demonstrate quantum supremacy, the tipping point where QC is faster than the fastest classical alternative for a particular problem. Because error correction techniques will be central to QC and will be the most expensive component of quantum computation, choosing the lowest-overhead error correction scheme is critical to overall QC success. This paper evaluates two established quantum error correction codes---planar and double-defect surface codes---using a set of compilation, scheduling and network simulation tools. In considering scalable methods for optimizing both codes, we do so in the context of a full microarchitectural and compiler analysis. Contrary to previous predictions, we find that the simpler planar codes are sometimes more favorable for implementation on superconducting quantum computers, especially under conditions of high communication congestion.Comment: 14 pages, 9 figures, The 50th Annual IEEE/ACM International Symposium on Microarchitectur

Event-based Vision: A Survey

Event cameras are bio-inspired sensors that differ from conventional frame cameras: Instead of capturing images at a fixed rate, they asynchronously measure per-pixel brightness changes, and output a stream of events that encode the time, location and sign of the brightness changes. Event cameras offer attractive properties compared to traditional cameras: high temporal resolution (in the order of microseconds), very high dynamic range (140 dB vs. 60 dB), low power consumption, and high pixel bandwidth (on the order of kHz) resulting in reduced motion blur. Hence, event cameras have a large potential for robotics and computer vision in challenging scenarios for traditional cameras, such as low-latency, high speed, and high dynamic range. However, novel methods are required to process the unconventional output of these sensors in order to unlock their potential. This paper provides a comprehensive overview of the emerging field of event-based vision, with a focus on the applications and the algorithms developed to unlock the outstanding properties of event cameras. We present event cameras from their working principle, the actual sensors that are available and the tasks that they have been used for, from low-level vision (feature detection and tracking, optic flow, etc.) to high-level vision (reconstruction, segmentation, recognition). We also discuss the techniques developed to process events, including learning-based techniques, as well as specialized processors for these novel sensors, such as spiking neural networks. Additionally, we highlight the challenges that remain to be tackled and the opportunities that lie ahead in the search for a more efficient, bio-inspired way for machines to perceive and interact with the world