Overcoming the Challenges for Multichip Integration: A Wireless Interconnect Approach

The physical limitations in the area, power density, and yield restrict the scalability of the single-chip multicore system to a relatively small number of cores. Instead of having a large chip, aggregating multiple smaller chips can overcome these physical limitations. Combining multiple dies can be done either by stacking vertically or by placing side-by-side on the same substrate within a single package. However, in order to be widely accepted, both multichip integration techniques need to overcome significant challenges. In the horizontally integrated multichip system, traditional inter-chip I/O does not scale well with technology scaling due to limitations of the pitch. Moreover, to transfer data between cores or memory components from one chip to another, state-of-the-art inter-chip communication over wireline channels require data signals to travel from internal nets to the peripheral I/O ports and then get routed over the inter-chip channels to the I/O port of the destination chip. Following this, the data is finally routed from the I/O to internal nets of the target chip over a wireline interconnect fabric. This multi-hop communication increases energy consumption while decreasing data bandwidth in a multichip system. On the other hand, in vertically integrated multichip system, the high power density resulting from the placement of computational components on top of each other aggravates the thermal issues of the chip leading to degraded performance and reduced reliability. Liquid cooling through microfluidic channels can provide cooling capabilities required for effective management of chip temperatures in vertical integration. However, to reduce the mechanical stresses and at the same time, to ensure temperature uniformity and adequate cooling competencies, the height and width of the microchannels need to be increased. This limits the area available to route Through-Silicon-Vias (TSVs) across the cooling layers and make the co-existence and co-design of TSVs and microchannels extreamly challenging. Research in recent years has demonstrated that on-chip and off-chip wireless interconnects are capable of establishing radio communications within as well as between multiple chips. The primary goal of this dissertation is to propose design principals targeting both horizontally and vertically integrated multichip system to provide high bandwidth, low latency, and energy efficient data communication by utilizing mm-wave wireless interconnects. The proposed solution has two parts: the first part proposes design methodology of a seamless hybrid wired and wireless interconnection network for the horizontally integrated multichip system to enable direct chip-to-chip communication between internal cores. Whereas the second part proposes a Wireless Network-on-Chip (WiNoC) architecture for the vertically integrated multichip system to realize data communication across interlayer microfluidic coolers eliminating the need to place and route signal TSVs through the cooling layers. The integration of wireless interconnect will significantly reduce the complexity of the co-design of TSV based interconnects and microchannel based interlayer cooling. Finally, this dissertation presents a combined trade-off evaluation of such wireless integration system in both horizontal and vertical sense and provides future directions for the design of the multichip system

Parallel CNN-ELM: A Multiclass Classification of Chest X-Ray Images to Identify Seventeen Lung Diseases Including COVID-19

Numerous epidemic lung diseases such as COVID-19, tuberculosis (TB), and pneumonia have spread over the world, killing millions of people. Medical specialists have experienced challenges in correctly identifying these diseases due to their subtle differences in Chest X-ray images (CXR). To assist the medical experts, this study proposed a computer-aided lung illness identification method based on the CXR images. For the first time, 17 different forms of lung disorders were considered and the study was divided into six trials with each containing two, two, three, four, fourteen, and seventeen different forms of lung disorders. The proposed framework combined robust feature extraction capabilities of a lightweight parallel convolutional neural network (CNN) with the classification abilities of the extreme learning machine algorithm named CNN-ELM. An optimistic accuracy of 90.92% and an area under the curve (AUC) of 96.93% was achieved when 17 classes were classified side by side. It also accurately identified COVID-19 and TB with 99.37% and 99.98% accuracy, respectively, in 0.996 microseconds for a single image. Additionally, the current results also demonstrated that the framework could outperform the existing state-of-the-art (SOTA) models. On top of that, a secondary conclusion drawn from this study was that the prospective framework retained its effectiveness over a range of real-world environments, including balanced-unbalanced or large-small datasets, large multiclass or simple binary class, and high- or low-resolution images. A prototype Android App was also developed to establish the potential of the framework in real-life implementation

The Advances, Challenges and Future Possibilities of Millimeter-Wave Chip-to-Chip Interconnections for Multi-Chip Systems

With aggressive scaling of device geometries, density of manufacturing faults is expected to increase. Therefore, yield of complex Multi-Processor Systems-on-Chips (MP-SoCs) will decrease due to higher probability of manufacturing defects especially, in dies with large area. Therefore, disintegration of large SoCs into smaller chips called chiplets will improve yield and cost of complex platform-based systems. This will also provide functional flexibility, modular scalability as well as the capability to integrate heterogeneous architectures and technologies in a single unit. However, with scaling of the number of chiplets in such a system, the shared resources in the system such as the interconnection fabric and memory modules will become performance bottlenecks. Additionally, the integration of heterogeneous chiplets operating at different frequencies and voltages can be challenging. State-of-the-art inter-chip communication requires power-hungry high-speed I/O circuits and data transfer over long wired traces on substrates. This increases energy consumption and latency while decreasing data bandwidth for chip-to-chip communication. In this paper, we explore the advances and the challenges of interconnecting a multi-chip system with millimeter-wave (mm-wave) wireless interconnects from a variety of perspectives spanning multiple aspects of the wireless interconnection design. Our discussion on the recent advances include aspects such as interconnection topology, physical layer, Medium Access Control (MAC) and routing protocols. We also present some potential paradigm-shifting applications as well as complementary technologies of wireless inter-chip communications

Fatty acid profile emphasizing trans-fatty acids in commercially available soybean and palm oils and its probable intake in Bangladesh

The study aimed to determine the trans-fat content in branded and unbranded soybean oil (SBO) and palm oil (PO) in nationally representative samples of Bangladesh. To our knowledge, this is the first comprehensive study reporting the Trans fatty acid (TFA) content in commonly consumed SBO and PO in Bangladesh. 106 composites (SBO 67, PO 39) were analyzed by GC–MS using Association of Official Analytical Chemists (AOAC) Methodology 996.06. According to the study, TFA (>2 %) was detected in 66.7 % of branded and 24.5 % of unbranded SBO samples, but in none of the palm oil samples. The average TFA contents in branded and unbranded SBO were 2.79 % (ranging from 0.42 % to 4.84 %) and 1.70 % (ranging from 0 %-4.25 %) respectively. Total TFA ranged from 0 %-1.61 % with a mean of 0.9 % and 0.61 % for branded and unbranded PO samples, respectively. From a daily intake of 27 g oil, Bangladeshi population has a probable TFA consumption of 0.75 g/day and 0.46 g/day from branded SBO and PO, respectively. This study generated evidence about the presence of an elevated level of TFA in edible oil, which should be strictly monitored