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Leveraging Strength-Based Dynamic Information Flow Analysis to Enhance Data Value Prediction
Value prediction is a technique to increase parallelism by attempting to overcome serialization constraints caused by true data dependences. By predicting the outcome of an instruction before it executes, value prediction allows data dependent ...
When Prefetching Works, When It Doesn’t, and Why
In emerging and future high-end processor systems, tolerating increasing cache miss latency and properly managing memory bandwidth will be critical to achieving high performance. Prefetching, in both hardware and software, is among our most important ...
Dataflow Tomography: Information Flow Tracking For Understanding and Visualizing Full Systems
It is not uncommon for modern systems to be composed of a variety of interacting services, running across multiple machines in such a way that most developers do not really understand the whole system. As abstraction is layered atop abstraction, ...
Improving System Energy Efficiency with Memory Rank Subsetting
VLSI process technology scaling has enabled dramatic improvements in the capacity and peak bandwidth of DRAM devices. However, current standard DDRx DIMM memory interfaces are not well tailored to achieve high energy efficiency and performance in modern ...
Comparability Graph Coloring for Optimizing Utilization of Software-Managed Stream Register Files for Stream Processors
The stream processors represent a promising alternative to traditional cache-based general-purpose processors in achieving high performance in stream applications (media and some scientific applications). In a stream programming model for stream ...
A Massively Parallel, Energy Efficient Programmable Accelerator for Learning and Classification
Applications that use learning and classification algorithms operate on large amounts of unstructured data, and have stringent performance constraints. For such applications, the performance of general purpose processors scales poorly with data size ...