As the trends of process scaling make memory systems an even more crucial bottleneck, the
importance of latency hiding techniques such as prefetching grows further. However, naively …

Data movement between the CPU and main memory is a first-order obstacle against improv
ing performance, scalability, and energy efficiency in modern systems. Computer systems …

Past research has proposed numerous hardware prefetching techniques, most of which rely
on exploiting one specific type of program context information (eg, program counter …

Pointer chasing is a fundamental operation, used by many important data-intensive
applications (eg, databases, key-value stores, graph processing workloads) to traverse …

The instruction-level parallelism found in a conventional instruction stream is limited. Studies
have shown the limits of processor utilization even for today's superscalar microprocessors …

Machine learning, graph analytics and sparse linear algebra-based applications are
dominated by irregular memory accesses resulting from following edges in a graph or non …

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Irregular workloads are typically bottlenecked by the memory system. These workloads often
use sparse data representations, eg, compressed sparse row/column (CSR/CSC), to …

Hardly predictable data addresses in many irregular applications have rendered prefetching
ineffective. In many cases, the only accurate way to predict these addresses is to directly …

The performance of memory-bound commercial applicationssuch as databases is limited by
increasing memory latencies. Inthis paper, we show that exploiting memory-level parallelism …