Large graph processing has gained great attention in recent years due to its broad applicability from machine learning to social science. Large real-world graphs, however, are inherently difficult to process efficiently, not only due to their large …
OpenCL FPGA has recently gained great popularity with emerging needs for workload acceleration such as Convolutional Neural Network (CNN), which is the most popular deep learning architecture in the domain of computer vision. While OpenCL enhances …
Driven by recent advances in resistive random-access memory (RRAM), there have been growing interests in exploring alternative computing concept, i.e., in-memory processing, to address the classical von Neumann bottlenecks. Despite of their great …
This work demonstrates the first fabricated nonvolatile TCAM using 2-transistor/2-resistive-storage (2T-2R) cells to achieve 10× smaller cell size than SRAM-based TCAMs at the same technology node. The test chip was designed and fabricated in IBM …
DRAM-based main memories have read operations that destroy the read data, and as a result, must buffer large amounts of data on each array access to keep chip costs low. Unfortunately, system-level trends such as increased memory contention in …