Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Rapidly processing high-velocity text data is critical for many technical and business applications. Widely used software solutions for processing these large text corpora target disk-resident data and rely on pre-computed indexes and large clusters to achieve high performance. Hover, greater capacity and falling costs are enabling a shift to RAM-resident data sets. The enormous bandwidth of RAM can facilitate scan operations that are competitive with pre-computed indexes for interactive, ad-hoc queries. Hover, software approaches for processing these large text corpora fall far short of saturating available bandwidth and meeting peak scan rates possible on modern memory systems. ,  present HAWK, a hardware accelerator for ad hoc queries against large in-memory logs. HAWK comprises a stall-free hardware pipeline that scans input data at a constant rate, examining multiple input characters in parallel during a single accelerator clock cycle.  describe a 1GHz 32-characterwide HAWK design targeting ASIC implementation, designed to process data at 32GB/s (up to two orders of magnitude faster than software solutions), and demonstrate a scaled-down FPGA prototype that operates at 100MHz with 4-wide parallelism, which processes at 400MB/s (13× faster than software grep for large multi-pattern scans).
['Prateek Tandon', 'Faissal M. Sleiman', 'Michael J. Cafarella', 'Thomas F. Wenisch']
I am writing a research paper on a idea HAWK: Hardware support for unstructured log processing
[{"from": "human", "value": "I am writing a research paper on a idea HAWK: Hardware support for unstructured log processing"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Rapidly processing high-velocity text data is critical for many technical and business applications. Widely used software solutions for processing these large text corpora target disk-resident data and rely on pre-computed indexes and large clusters to achieve high performance. Hover, greater capacity and falling costs are enabling a shift to RAM-resident data sets. The enormous bandwidth of RAM can facilitate scan operations that are competitive with pre-computed indexes for interactive, ad-hoc queries. Hover, software approaches for processing these large text corpora fall far short of saturating available bandwidth and meeting peak scan rates possible on modern memory systems. ,  present HAWK, a hardware accelerator for ad hoc queries against large in-memory logs. HAWK comprises a stall-free hardware pipeline that scans input data at a constant rate, examining multiple input characters in parallel during a single accelerator clock cycle.  describe a 1GHz 32-characterwide HAWK design targeting ASIC implementation, designed to process data at 32GB/s (up to two orders of magnitude faster than software solutions), and demonstrate a scaled-down FPGA prototype that operates at 100MHz with 4-wide parallelism, which processes at 400MB/s (13\u00d7 faster than software grep for large multi-pattern scans)."}]