Managing shared last-level cache in a heterogeneous multicore processor

@article{Mekkat2013ManagingSL,
  title={Managing shared last-level cache in a heterogeneous multicore processor},
  author={Vineeth Mekkat and Anup Holey and Pen-Chung Yew and Antonia Zhai},
  journal={Proceedings of the 22nd International Conference on Parallel Architectures and Compilation Techniques},
  year={2013},
  pages={225-234}
}
Heterogeneous multicore processors that integrate CPU cores and data-parallel accelerators such as GPU cores onto the same die raise several new issues for sharing various on-chip resources. The shared last-level cache (LLC) is one of the most important shared resources due to its impact on performance. Accesses to the shared LLC in heterogeneous multicore processors can be dominated by the GPU due to the significantly higher number of threads supported. Under current cache management policies… CONTINUE READING

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References

Publications referenced by this paper.
SHOWING 1-10 OF 10 REFERENCES

Sampling Dead Block Prediction for Last-Level Caches

  • 2010 43rd Annual IEEE/ACM International Symposium on Microarchitecture
  • 2010
VIEW 13 EXCERPTS
HIGHLY INFLUENTIAL

Runtime cache bypassing

T. JOHNSON, D. CONNORS, M. MERTEN, HWU, W.-M
  • IEEE Transactions on Computers
  • 1999
VIEW 13 EXCERPTS
HIGHLY INFLUENTIAL

Multi2Sim: A simulation framework for CPU-GPU computing

  • 2012 21st International Conference on Parallel Architectures and Compilation Techniques (PACT)
  • 2012
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

TAP: A TLP-aware cache management policy for a CPU-GPU heterogeneous architecture

  • IEEE International Symposium on High-Performance Comp Architecture
  • 2012
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

Utility-Based Cache Partitioning: A Low-Overhead, High-Performance, Runtime Mechanism to Partition Shared Caches

  • 2006 39th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO'06)
  • 2006
VIEW 13 EXCERPTS
HIGHLY INFLUENTIAL

AMD Fusion Family of APUs: Enabling a Superior, Immersive PC Experience

N. BROOKWOOD
  • AMD White Paper
  • 2010
VIEW 3 EXCERPTS
HIGHLY INFLUENTIAL