Abstract: In the Solid-State-Drive (SSD) performance, whether
the data has been well parallelized is an important factor. SSD
parallelization is affected by allocation scheme and it is directly
connected to SSD performance. There are dynamic allocation and
static allocation in representative allocation schemes. Dynamic
allocation is more adaptive in exploiting write operation parallelism,
while static allocation is better in read operation parallelism.
Therefore, it is hard to select the appropriate allocation scheme when
the workload is mixed read and write operations. We simulated
conditions on a few mixed data patterns and analyzed the results to
help the right choice for better performance. As the results, if data
arrival interval is long enough prior operations to be finished and
continuous read intensive data environment static allocation is more
suitable. Dynamic allocation performs the best on write performance
and random data patterns.
Abstract: OpenMP is an API for parallel programming model of shared memory multiprocessors. Novice OpenMP programmers often produce the code that compiler cannot find human errors. It was investigated how compiler coped with the common mistakes that can occur in OpenMP code. The latest version(4.4.3) of GCC is used for this research. It was found that GCC compiled the codes without any errors or warnings. In this paper the programming aid tool is presented for OpenMP programs. It can check 12 common mistakes that novice programmer can commit during the programming of OpenMP. It was demonstrated that the programming aid tool can detect the various common mistakes that GCC failed to detect.
Abstract: This paper considers the problem of finding low cost
chip set for a minimum cost partitioning of a large logic circuits. Chip
sets are selected from a given library. Each chip in the library has a
different price, area, and I/O pin. We propose a low cost chip set
selection algorithm. Inputs to the algorithm are a netlist and a chip
information in the library. Output is a list of chip sets satisfied with
area and maximum partitioning number and it is sorted by cost. The
algorithm finds the sorted list of chip sets from minimum cost to
maximum cost. We used MCNC benchmark circuits for experiments.
The experimental results show that all of chip sets found satisfy the
multiple partitioning constraints.