Kim Hazelwood
Cited by
Cited by
Pin: building customized program analysis tools with dynamic instrumentation
CK Luk, R Cohn, R Muth, H Patil, A Klauser, G Lowney, S Wallace, ...
Acm sigplan notices 40 (6), 190-200, 2005
Applied machine learning at facebook: A datacenter infrastructure perspective
K Hazelwood, S Bird, D Brooks, S Chintala, U Diril, D Dzhulgakov, ...
2018 IEEE International Symposium on High Performance Computer Architecture …, 2018
Where is the data? Why you cannot debate CPU vs. GPU performance without the answer
C Gregg, K Hazelwood
(IEEE ISPASS) IEEE International Symposium on Performance Analysis of …, 2011
Profiling a warehouse-scale computer
S Kanev, JP Darago, K Hazelwood, P Ranganathan, T Moseley, GY Wei, ...
Proceedings of the 42nd Annual International Symposium on Computer …, 2015
Machine learning at facebook: Understanding inference at the edge
CJ Wu, D Brooks, K Chen, D Chen, S Choudhury, M Dukhan, ...
2019 IEEE International Symposium on High Performance Computer Architecture …, 2019
Analyzing parallel programs with pin
M Bach, M Charney, R Cohn, E Demikhovsky, T Devor, K Hazelwood, ...
Computer 43 (3), 34-41, 2010
Mlperf training benchmark
P Mattson, C Cheng, C Coleman, G Diamos, P Micikevicius, D Patterson, ...
arXiv preprint arXiv:1910.01500, 2019
Superpin: Parallelizing dynamic instrumentation for real-time performance
S Wallace, K Hazelwood
International Symposium on Code Generation and Optimization (CGO'07), 209-220, 2007
Reducing DRAM footprint with NVM in Facebook
A Eisenman, D Gardner, I AbdelRahman, J Axboe, S Dong, K Hazelwood, ...
Proceedings of the Thirteenth EuroSys Conference, 1-13, 2018
Enabling task parallelism in the cuda scheduler
M Guevara, C Gregg, K Hazelwood, K Skadron
Workshop on Programming Models for Emerging Architectures 9, 2009
Fine-Grained Resource Sharing for Concurrent {GPGPU} Kernels
C Gregg, J Dorn, K Hazelwood, K Skadron
4th {USENIX} Workshop on Hot Topics in Parallelism (HotPar 12), 2012
A dynamic binary instrumentation engine for the arm architecture
K Hazelwood, A Klauser
Proceedings of the 2006 international conference on Compilers, architecture …, 2006
The architectural implications of facebook's dnn-based personalized recommendation
U Gupta, CJ Wu, X Wang, M Naumov, B Reagen, D Brooks, B Cottel, ...
2020 IEEE International Symposium on High Performance Computer Architecture …, 2020
Deep learning inference in facebook data centers: Characterization, performance optimizations and hardware implications
J Park, M Naumov, P Basu, S Deng, A Kalaiah, D Khudia, J Law, P Malani, ...
arXiv preprint arXiv:1811.09886, 2018
Adaptive online context-sensitive inlining
K Hazelwood, D Grove
International Symposium on Code Generation and Optimization, 2003. CGO 2003 …, 2003
Tradeoffs between power management and tail latency in warehouse-scale applications
S Kanev, K Hazelwood, GY Wei, D Brooks
2014 IEEE International Symposium on Workload Characterization (IISWC), 31-40, 2014
Dynamic heterogeneous scheduling decisions using historical runtime data
C Gregg, M Boyer, K Hazelwood, K Skadron
Workshop on Applications for Multi-and Many-Core Processors (A4MMC), 1-12, 2011
Improving region selection in dynamic optimization systems
D Hiniker, K Hazelwood, MD Smith
38th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO'05 …, 2005
Eliminating voltage emergencies via microarchitectural voltage control feedback and dynamic optimization
K Hazelwood, D Brooks
Proceedings of the 2004 international symposium on Low power electronics and …, 2004
Code cache management schemes for dynamic optimizers
K Hazelwood, MD Smith
Proceedings Sixth Annual Workshop on Interaction between Compilers and …, 2002
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