X-SRAM: Enabling In-Memory Boolean Computations in CMOS Static Random Access Memories

Silicon-based Static Random Access Memories (SRAM) and digital Boolean logic have been the workhorse of the state-of-art computing platforms. Despite tremendous strides in scaling the ubiquitous metal-oxide-semiconductor transistor, the underlying \textit{von-Neumann} computing architecture has remained unchanged. The limited throughput and energy-efficiency of the state-of-art computing systems, to a large extent, results from the well-known \textit{von-Neumann bottleneck}. The energy and throughput inefficiency of the von-Neumann machines have been accentuated in recent times due to the present emphasis on data-intensive applications like artificial intelligence, machine learning \textit{etc}. A possible approach towards mitigating the overhead associated with the von-Neumann bottleneck is to enable \textit{in-memory} Boolean computations. In this manuscript, we present an augmented version of the conventional SRAM bit-cells, called \textit{the X-SRAM}, with the ability to perform in-memory, vector Boolean computations, in addition to the usual memory storage operations. We propose at least six different schemes for enabling in-memory vector computations including NAND, NOR, IMP (implication), XOR logic gates with respect to different bit-cell topologies $-$ the 8T cell and the 8$^+$T Differential cell. In addition, we also present a novel \textit{`read-compute-store'} scheme, wherein the computed Boolean function can be directly stored in the memory without the need of latching the data and carrying out a subsequent write operation. The feasibility of the proposed schemes has been verified using predictive transistor models and Monte-Carlo variation analysis.Comment: This article has been accepted in a future issue of IEEE Transactions on Circuits and Systems-I: Regular Paper

Hierarchical cluster analysis with bootstrap resampling method was performed on the complete set of organisms (columns of the phylogenetic profile matrix)

<p><b>Copyright information:</b></p><p>Taken from "A global gene evolution analysis on family using phylogenetic profile"</p><p>http://www.biomedcentral.com/1471-2105/8/S1/S23</p><p>BMC Bioinformatics 2007;8(Suppl 1):S23-S23.</p><p>Published online 8 Mar 2007</p><p>PMCID:PMC1885853.</p><p></p> The number of genes identified in each organism (with a similarity measure greater than zero) is reported as a gray histogram below the dendrogram. Organism taxonomies are highlighted with different colors: proteobacteria in blue, proteobacteria in red, proteobacteria in green, proteobacteria in light blue and others in black

Two-way hierarchical cluster analysis performed on prophage and transposase proteins

<p><b>Copyright information:</b></p><p>Taken from "A global gene evolution analysis on family using phylogenetic profile"</p><p>http://www.biomedcentral.com/1471-2105/8/S1/S23</p><p>BMC Bioinformatics 2007;8(Suppl 1):S23-S23.</p><p>Published online 8 Mar 2007</p><p>PMCID:PMC1885853.</p><p></p> The blue bars highlight the more interesting clusters of genes such as for example the CTX prophage

Two-way hierarchical cluster analysis of the entire phylogenetic profile matrix (panel A)

<p><b>Copyright information:</b></p><p>Taken from "A global gene evolution analysis on family using phylogenetic profile"</p><p>http://www.biomedcentral.com/1471-2105/8/S1/S23</p><p>BMC Bioinformatics 2007;8(Suppl 1):S23-S23.</p><p>Published online 8 Mar 2007</p><p>PMCID:PMC1885853.</p><p></p> Panel B: dendrogram selection zoom of highly conserved genes shared among all the organisms; panel C: genes conserved mostly among ; panel D: genes specific of family

The blue line represents the number of genes, while the red line reports the number of gene clusters shared by an increasing number of genomes

<p><b>Copyright information:</b></p><p>Taken from "A global gene evolution analysis on family using phylogenetic profile"</p><p>http://www.biomedcentral.com/1471-2105/8/S1/S23</p><p>BMC Bioinformatics 2007;8(Suppl 1):S23-S23.</p><p>Published online 8 Mar 2007</p><p>PMCID:PMC1885853.</p><p></p

Number of gene clusters identified only in family; the number of genomes is reported on the x axis and the amount of shared genes is reported on the y axis

<p><b>Copyright information:</b></p><p>Taken from "A global gene evolution analysis on family using phylogenetic profile"</p><p>http://www.biomedcentral.com/1471-2105/8/S1/S23</p><p>BMC Bioinformatics 2007;8(Suppl 1):S23-S23.</p><p>Published online 8 Mar 2007</p><p>PMCID:PMC1885853.</p><p></p> In the first histogram, for example, there are 11 groups of each composed by 2 genomes

Data_Sheet_2_Hydrogen-Fueled Microbial Pathways in Biogas Upgrading Systems Revealed by Genome-Centric Metagenomics.XLSX

<p>Biogas upgrading via carbon dioxide hydrogenation is an emerging technology for electrofuel production. The biomethanation efficiency is strongly dependent on a balanced microbial consortium, whose high- resolution characterization along with their functional potential and interactions are pivotal for process optimization. The present work is the first genome-centric metagenomic study on mesophilic and thermophilic biogas upgrading reactors aiming to define the metabolic profile of more than 200 uncultivated microbes involved in hydrogen assisted methanogenesis. The outcomes from predictive functional analyses were correlated with microbial abundance variations to clarify the effect of process parameters on the community. The operational temperature significantly influenced the microbial richness of the reactors, while the H₂ addition distinctively alternated the abundance of the taxa. Two different Methanoculleus species (one mesophilic and one thermophilic) were identified as the main responsible ones for methane metabolism. Finally, it was demonstrated that the addition of H₂ exerted a selective pressure on the concerted or syntrophic interactions of specific microbes functionally related to carbon fixation, propionate and butanoate metabolisms. Novel bacteria were identified as candidate syntrophic acetate oxidizers (e.g., Tepidanaerobacter sp. DTU063), while the addition of H₂ favored the proliferation of potential homoacetogens (e.g., Clostridia sp. DTU183). Population genomes encoding genes of Wood-Ljungdahl pathway were mainly thermophilic, while propionate degraders were mostly identified at mesophilic conditions. Finally, putative syntrophic interactions were identified between microbes that have either versatile metabolic abilities or are obligate/facultative syntrophs.</p

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Additional file 6. Functional characterization of the GBs according to COG. (“COG_gene_numb” worksheet) GBs were annotated using COG. Numbers refer to the genes identified on each GB for each COG category. The COG categories are reported in columns (C–AA), the GBs are reported in rows (2–107). (“COG_perc” worksheet) Percentages of genes belonging to COG categories are calculated with respect to the total number of COG results for each GB (note that some genes belong to more than one COG category). In red and green are highlighted, for each COG category, the GBs having the 10 highest and the 10 lowest percentages. (“hypergeometric” worksheet). For each GB and each COG functional category, the P value obtained from hypergeometric distribution is reported

Data_Sheet_1_Hydrogen-Fueled Microbial Pathways in Biogas Upgrading Systems Revealed by Genome-Centric Metagenomics.docx

<p>Biogas upgrading via carbon dioxide hydrogenation is an emerging technology for electrofuel production. The biomethanation efficiency is strongly dependent on a balanced microbial consortium, whose high- resolution characterization along with their functional potential and interactions are pivotal for process optimization. The present work is the first genome-centric metagenomic study on mesophilic and thermophilic biogas upgrading reactors aiming to define the metabolic profile of more than 200 uncultivated microbes involved in hydrogen assisted methanogenesis. The outcomes from predictive functional analyses were correlated with microbial abundance variations to clarify the effect of process parameters on the community. The operational temperature significantly influenced the microbial richness of the reactors, while the H₂ addition distinctively alternated the abundance of the taxa. Two different Methanoculleus species (one mesophilic and one thermophilic) were identified as the main responsible ones for methane metabolism. Finally, it was demonstrated that the addition of H₂ exerted a selective pressure on the concerted or syntrophic interactions of specific microbes functionally related to carbon fixation, propionate and butanoate metabolisms. Novel bacteria were identified as candidate syntrophic acetate oxidizers (e.g., Tepidanaerobacter sp. DTU063), while the addition of H₂ favored the proliferation of potential homoacetogens (e.g., Clostridia sp. DTU183). Population genomes encoding genes of Wood-Ljungdahl pathway were mainly thermophilic, while propionate degraders were mostly identified at mesophilic conditions. Finally, putative syntrophic interactions were identified between microbes that have either versatile metabolic abilities or are obligate/facultative syntrophs.</p

Data_Sheet_3_Hydrogen-Fueled Microbial Pathways in Biogas Upgrading Systems Revealed by Genome-Centric Metagenomics.ZIP

<p>Biogas upgrading via carbon dioxide hydrogenation is an emerging technology for electrofuel production. The biomethanation efficiency is strongly dependent on a balanced microbial consortium, whose high- resolution characterization along with their functional potential and interactions are pivotal for process optimization. The present work is the first genome-centric metagenomic study on mesophilic and thermophilic biogas upgrading reactors aiming to define the metabolic profile of more than 200 uncultivated microbes involved in hydrogen assisted methanogenesis. The outcomes from predictive functional analyses were correlated with microbial abundance variations to clarify the effect of process parameters on the community. The operational temperature significantly influenced the microbial richness of the reactors, while the H₂ addition distinctively alternated the abundance of the taxa. Two different Methanoculleus species (one mesophilic and one thermophilic) were identified as the main responsible ones for methane metabolism. Finally, it was demonstrated that the addition of H₂ exerted a selective pressure on the concerted or syntrophic interactions of specific microbes functionally related to carbon fixation, propionate and butanoate metabolisms. Novel bacteria were identified as candidate syntrophic acetate oxidizers (e.g., Tepidanaerobacter sp. DTU063), while the addition of H₂ favored the proliferation of potential homoacetogens (e.g., Clostridia sp. DTU183). Population genomes encoding genes of Wood-Ljungdahl pathway were mainly thermophilic, while propionate degraders were mostly identified at mesophilic conditions. Finally, putative syntrophic interactions were identified between microbes that have either versatile metabolic abilities or are obligate/facultative syntrophs.</p