Priyanka Gaur | Council for Scientific and Industrial Research (CSIR) (original) (raw)
Priyanka Gaur
Student of Information Technology
B.K.B.I.E.T,Pilani.
Supervisors: hemant gaur
Address: India
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Papers by Priyanka Gaur
We propose extended versions are presented that elaborates the effect of the design’s degrees of ... more We propose extended versions are presented that elaborates the effect of the
design’s degrees of freedom, and the effect on non uniformity of input patterns
on energy consumption and the performance. The proposed architecture is
based on a recently refined sparse clustered networks using binary connections
that on-average eliminates most of the parallel comparisons performed during a
search. Given an input tag, the proposed architecture computes a few
possibilities for the location of the matched tag and performs the comparisons
on them to locate a single valid match, and also by using a reordered overlapped
search mechanism, most mismatches can be found by searching a few bits of a
search word. Following a selection of design parameters, such as the number of
CAM entries, the energy consumption and the search delay of the proposed
design are 8%, and 26% of that of the conventional NAND architecture,
respectively, with a 10% area overhead.
Keywords: Associative memory, content-addressable memory (CAM), lowpower
computing, recurrent neural networks, binary connections.
In an unstructured P2P system, no rule exists that strictly defines where data is stored and whic... more In an unstructured P2P system, no rule exists that strictly defines where data is stored and which nodes are neighbors of each other. To find a specific data item, Gnutella used flooding, which is the Breadth First Search (BFS) of the overlay network graph with depth limit D. D refers to the system-wide maximum TTL of a message in terms of overlay hops. In this approach, the querying node sends the query request to all its neighbors. Each neighbor processes the query and returns the result if the data is found. This neighbor then forwards the query request further to all its neighbors except the querying node. This procedure continues until the depth limit D is reached. Flooding tries to find the maximum number of results within the ring that is centered at the querying node and has the radius: D-overlay-hops.
We propose extended versions are presented that elaborates the effect of the design’s degrees of ... more We propose extended versions are presented that elaborates the effect of the
design’s degrees of freedom, and the effect on non uniformity of input patterns
on energy consumption and the performance. The proposed architecture is
based on a recently refined sparse clustered networks using binary connections
that on-average eliminates most of the parallel comparisons performed during a
search. Given an input tag, the proposed architecture computes a few
possibilities for the location of the matched tag and performs the comparisons
on them to locate a single valid match, and also by using a reordered overlapped
search mechanism, most mismatches can be found by searching a few bits of a
search word. Following a selection of design parameters, such as the number of
CAM entries, the energy consumption and the search delay of the proposed
design are 8%, and 26% of that of the conventional NAND architecture,
respectively, with a 10% area overhead.
Keywords: Associative memory, content-addressable memory (CAM), lowpower
computing, recurrent neural networks, binary connections.
In an unstructured P2P system, no rule exists that strictly defines where data is stored and whic... more In an unstructured P2P system, no rule exists that strictly defines where data is stored and which nodes are neighbors of each other. To find a specific data item, Gnutella used flooding, which is the Breadth First Search (BFS) of the overlay network graph with depth limit D. D refers to the system-wide maximum TTL of a message in terms of overlay hops. In this approach, the querying node sends the query request to all its neighbors. Each neighbor processes the query and returns the result if the data is found. This neighbor then forwards the query request further to all its neighbors except the querying node. This procedure continues until the depth limit D is reached. Flooding tries to find the maximum number of results within the ring that is centered at the querying node and has the radius: D-overlay-hops.