Publications

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Proxy applications, or proxies, are simple applications meant to exercise systems in a way that mimics real applications (their parents). However, characterizing the relationship between the behavior of parent and proxy applications is not an easy task. In prior work [1], we presented a data-driven methodology to characterize the relationship between parent and proxy applications based on collecting runtime data from both and then using data analytics to find their correspondence or divergence. We showed that it worked well for hardware counter data, but our initial attempt using MPI function data was less satisfactory. In this paper, we present an exploratory effort at making an improved quantification of the correspondence of communication behavior for proxies and their respective parent applications. We present experimental evidence of positive results using four proxy applications from the current ECP Proxy Application Suite and their corresponding parent applications (in the ECP application portfolio). Results show that each proxy analyzed is representative of its parent with respect to communication data. In conjunction with our method presented in [1] (correspondence between computation and memory behavior), we get a strong understanding of how well a proxy predicts the comprehensive performance of its parent.

Proxy applications, or proxies, are simple applications meant to exercise systems in a way that mimics real applications (their parents). However, characterizing the relationship between the behavior of parent and proxy applications is not an easy task. In prior work [1], we presented a data-driven methodology to characterize the relationship between parent and proxy applications based on collecting runtime data from both and then using data analytics to find their correspondence or divergence. We showed that it worked well for hardware counter data, but our initial attempt using MPI function data was less satisfactory. In this paper, we present an exploratory effort at making an improved quantification of the correspondence of communication behavior for proxies and their respective parent applications. We present experimental evidence of positive results using four proxy applications from the current ECP Proxy Application Suite and their corresponding parent applications (in the ECP application portfolio). Results show that each proxy analyzed is representative of its parent with respect to communication data. In conjunction with our method presented in [1] (correspondence between computation and memory behavior), we get a strong understanding of how well a proxy predicts the comprehensive performance of its parent.

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Continued progress in computing has augmented the quest for higher performance with a new quest for higher energy efficiency. This has led to the re-emergence of Processing-In-Memory (PIM) ar- chitectures that offer higher density and performance with some boost in energy efficiency. Past PIM work either integrated a standard CPU with a conventional DRAM to improve the CPU- memory link, or used a bit-level processor with Single Instruction Multiple Data (SIMD) control, but neither matched the energy consumption of the memory to the computation. We originally proposed to develop a new architecture derived from PIM that more effectively addressed energy efficiency for high performance scientific, data analytics, and neuromorphic applications. We also originally planned to implement a von Neumann architecture with arithmetic/logic units (ALUs) that matched the power consumption of an advanced storage array to maximize energy efficiency. Implementing this architecture in storage was our original idea, since by augmenting storage (in- stead of memory), the system could address both in-memory computation and applications that accessed larger data sets directly from storage, hence Processing-in-Memory-and-Storage (PIMS). However, as our research matured, we discovered several things that changed our original direc- tion, the most important being that a PIM that implements a standard von Neumann-type archi- tecture results in significant energy efficiency improvement, but only about a O(10) performance improvement. In addition to this, the emergence of new memory technologies moved us to propos- ing a non-von Neumann architecture, called Superstrider, implemented not in storage, but in a new DRAM technology called High Bandwidth Memory (HBM). HBM is a stacked DRAM tech- nology that includes a logic layer where an architecture such as Superstrider could potentially be implemented.

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Cache has long been used to minimize the latency of main memory accesses by storing frequently used data near the processor. Processor performance depends on the underlying cache performance. Therefore, significant research has been done to identify the most crucial metrics of cache performance. Although the majority of research focuses on measuring cache hit rates and data movement as the primary cache performance metrics, cache utilization is significantly important. We investigate the application’s locality using cache utilization metrics. In addition, we present cache utilization and traditional cache performance metrics as the program progresses providing detailed insights into the dynamic application behavior on parallel applications from four benchmark suites running on multiple cores. We explore cache utilization for APEX, Mantevo, NAS, and PARSEC, mostly scientific benchmark suites. Our results indicate that 40% of the data bytes in a cache line are accessed at least once before line eviction. Also, on average a byte is accessed two times before the cache line is evicted for these applications. Moreover, we present runtime cache utilization, as well as, conventional performance metrics that illustrate a holistic understanding of cache behavior. To facilitate this research, we build a memory simulator incorporated into the Structural Simulation Toolkit (Rodrigues et al. in SIGMETRICS Perform Eval Rev 38(4):37–42, 2011). Finally, our results suggest that variable cache line size can result in better performance and can also conserve power.

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