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Protean : Resource-efficient Instruction Prefetching
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- Hassan, Muhammad, 1990- (författare)
- Uppsala universitet,Avdelningen för datorteknik,Datorarkitektur och datorkommunikation
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- Park, Chang Hyun, Assistant Professor, 1989- (författare)
- Uppsala universitet,Avdelningen för datorteknik,Datorarkitektur och datorkommunikation,Datorteknik
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- Black-Schaffer, David, Professor (författare)
- Uppsala universitet,Avdelningen för datorteknik,Datorarkitektur och datorkommunikation
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(creator_code:org_t)
- Association for Computing Machinery (ACM), 2023
- 2023
- Engelska.
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Ingår i: The International Symposium on Memory Systems (MEMSYS '23). - : Association for Computing Machinery (ACM). - 9798400716447 ; , s. 1-13
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Abstract
Ämnesord
Stäng
- Increases in code footprint and control flow complexity have made low-latency instruction fetch challenging. Dedicated Instruction Prefetchers (DIPs) can provide performance gains (up to 5%) for a subset of applications that are poorly served by today’s ubiquitous Fetch-Directed Instruction Prefetching (FDIP). However, DIPs incur the significant overhead of in-core metadata storage (for all work- loads) and energy and performance loss from excess prefetches (for many workloads), leading to 11% of workloads actually losing performance. This work addresses how to provide the benefits of a DIP without its costs when the DIP cannot provide a benefit.Our key insight is that workloads that benefit from DIPs can tolerate increased Branch Target Buffer (BTB) misses. This allows us to dynamically re-purpose the existing BTB storage between the BTB and the DIP. We train a simple performance counter based decision tree to select the optimal configuration at runtime, which allows us to achieve different energy/performance optimization goals. As a result, we pay essentially no area overhead when a DIP is needed, and can use the larger BTB when it is beneficial, or even power it off when not needed.We look at our impact on two groups of benchmarks: those where the right configuration choice can improve performance or energy and those where the wrong choice could hurt them. For the benchmarks with improvement potential, when optimizing for performance, we are able to obtain 86% of the oracle potential, and when optimizing for energy, 98% of the potential, both while avoid- ing essentially all performance and energy losses on the remaining benchmarks. This demonstrates that our technique is able to dy- namically adapt to different performance/energy goals and obtain essentially all of the potential gains of DIP without the overheads they experience today.
Ämnesord
- TEKNIK OCH TEKNOLOGIER -- Elektroteknik och elektronik -- Datorsystem (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Electrical Engineering, Electronic Engineering, Information Engineering -- Computer Systems (hsv//eng)
Nyckelord
- Computer Science
- Datavetenskap
- Computer Systems Sciences
- Data- och systemvetenskap
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)
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