Feedback Directed Prefetching: Improving the Performance and Bandwidth-Efficiency of Hardware Prefetchers
By Santhosh Srinath, Onur Mutlu, Hyesoon Kim, Yale N. Patt. 2007 IEEE 13th International Symposium on High Performance Computer Architecture, 2007
378 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Hardware and Architecture, Information Systems
View Paper: https://www.semanticscholar.org/paper/bcbef8e1945b432a474089796300f2d20d011d6a
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Networks and Communications
- Onur Mutlu
- Vivek Seshadri
- Michael A. Kozuch
- Todd C. Mowry
- Mahmut Taylan Kandemir
- Adwait Jog
- Phillip B. Gibbons
- R. Iyer
In Hardware and Architecture
- Onur Mutlu
- Vivek Seshadri
- Michael A. Kozuch
- Todd C. Mowry
- Mahmut Taylan Kandemir
- Carole-Jean Wu
- Adwait Jog
- Phillip B. Gibbons
In Information Systems
- Onur Mutlu
- Margaret Martonosi
- Vivek Seshadri
- Todd C. Mowry
- Joel S. Emer
- Phillip B. Gibbons
- Michael A. Kozuch
- Carole-Jean Wu
Citations in the corpus
- SHiP: Signature-based Hit Predictor for high performance caching (2011, background): “Alternatively, studies have also shown that simply changing the re-reference prediction on cache insertions [10, 27, 29, 32] can significantly improve cache performance at very low hardware overhead.”
- OWL: cooperative thread array aware scheduling techniques for improving GPGPU performance (2013, background): “, [13, 23, 45, 52]) have been proposed within the context of CPU systems.”
- Base-delta-immediate compression: Practical data compression for on-chip caches (2012, methodology): “For multi-programmed workloads we use the weighted speedup [25] as the performance metric: For bandwidth consumption we use BPKI (bytes transferred over bus per thousand instructions [27]).”
- RowClone: Fast and energy-efficient in-DRAM bulk data copy and initialization (2013, neutral): “NumberofCores 2 4 8 NumberofWorkloads 138 50 40 WeightedSpeedup[14]Improvement 15% 20% 27% InstructionThroughputImprovement 14% 15% 25% HarmonicSpeedup[35]Improvement 13% 16% 29% MaximumSlowdown[12,29,30]Reduction 6% 12% 23% MemoryBandwidth/Instruction[49]Reduction 29% 27% 28% MemoryEnergy/Instru”
- Fairness via source throttling: a configurable and high-performance fairness substrate for multi-core memory systems (2010, neutral): “Several prior papers investigated how to handle prefetch requests in shared resources [Ebrahimi et al. 2009, 2011a; Srinath et al. 2007].”