The last decade has seen improvements in processor architecture that have enabled CPU
dies to pack 64 to 128 cores, compared to 4 to 8 cores only a few years ago. Applications …

The complexity and diversity of big data and AI workloads make understanding them difficult
and challenging. This paper proposes a new approachto modelling and characterizing big …

This work presents the first thorough quantitative study of the available instruction-level
parallelism, basic-block-granularity thread parallelism, and data movement, across the …

For the architecture community, reasonable simulation time is a strong requirement in
addition to performance data accuracy. However, emerging big data and AI workloads are …

Big data analytics plays an important role in almost all the fields nowadays. Whenever we
are in the critical care situation and we are in need of fast results from a complex procedures …

Communication patterns extracted from parallel programs can provide a valuable source of
information for parallel pattern detection, application auto-tuning, and runtime workload …

Several fundamental changes in technology indicate domain-specific hardware and
software co-design is the only path left. In this context, architecture, system, data …

In this paper, we present the performance analysis and design challenges of implementing a
fault-tolerant parallel exact motif mining algorithm leveraging the services provided by the …

Presented are two novel solutions addressing issues in the application of automated data
analysis techniques in the medical domain. The primary aim of our work is to provide …

Observing that large multithreaded applications with irregular data access patterns exhibit
very low memory bank-level parallelism (BLP) during their execution, we propose a novel …