Zobrazeno 1 - 10
of 23
pro vyhledávání: '"Debbie Marr"'
Autor:
Jonathan Chang, Debbie Marr, Ken Takeuchi, Samuel D. Naffziger, Shinichiro Shiratake, Thomas Burd, Henk Corporaal, Naresh R. Shanbhag, Eric Karl, Hugh Mair
Publikováno v:
ISSCC
General-purpose computing has derived performance gains from clock frequency and instructions-per-clock for over four decades; achieving an impressive ∼105 performance increase over the same timeframe. With the future of the traditional computing r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9944df1b606de6c23c308ae741fed9c7
https://doi.org/10.1109/isscc42613.2021.9366007
https://doi.org/10.1109/isscc42613.2021.9366007
Autor:
Bogdan Pasca, Dongup Kwon, Sergey Gribok, Gregory K. Chen, Eriko Nurvitadhi, Jaewoong Sim, Knag Phil, Martin Langhammer, Ram Krishnamurthy, Phillip Tomson, Debbie Marr, Aravind Dasu, Sumbul Huseyin Ekin, Ali Jafari, Raghavan Kumar, Andrew Boutros
Publikováno v:
FCCM
Interactive intelligent services, such as smart web search, are important datacenter workloads. They rely on dataintensive deep learning (DL) algorithms with strict latency constraints and thus require balancing both data movement and compute capabil
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8424fcfb0c47be38b3c9b06d624d3d87
https://doi.org/10.1109/fccm.2019.00035
https://doi.org/10.1109/fccm.2019.00035
Autor:
Eriko Nurvitadhi, Raghavan Kumar, Martin Langhammer, Ali Jafari, Gregory K. Chen, Jaewoong Sim, Phillip Tomson, Sergey Gribok, Debbie Marr, Ram Krishnamurthy, Aravind Dasu, Knag Phil, Andrew Boutros, Bogdan Pasca, Dongup Kwon, Sumbul Huseyin Ekin
Publikováno v:
FPGA
Interactive intelligent services (e.g., smart web search) are becoming essential datacenter workloads. They rely on data-intensive artificial intelligence (AI) algorithms that do not use batch computation due to their tight latency constraints. Since
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ec019e5424875aa387716e89b6152bec
https://doi.org/10.1145/3289602.3293943
https://doi.org/10.1145/3289602.3293943
Publikováno v:
IEEE Computer Architecture Letters. 15:85-88
The performance of user-facing applications is critical to client platforms. Many of these applications are event-driven and exhibit “bursty” behavior: the application is generally idle but generates bursts of activity in response to human intera
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::38fc29947fdbf4d3b48ae0ade9b73ab0
https://doi.org/10.1109/lca.2015.2456013
https://doi.org/10.1109/lca.2015.2456013
Autor:
Sergey Y. Shumarayev, Utku Aydonat, Asit K. Mishra, Aravind Dasu, Debbie Marr, Davor Capalija, Eriko Nurvitadhi, Kevin Nealis, Philip Colangelo, Jeffrey J. Cook, Andrew Ling
Publikováno v:
FPL
FPGAs or ASICs? FPGAs are extremely flexible while ASICs offer top efficiency. We believe that FPGAs and ASICs are better together, to offer flexibility and efficiency. We propose single-package heterogeneous 2.5D integration of FPGAs and ASICs, usin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::674a811fdf2e9387fbca489e3e43b30c
https://doi.org/10.1109/fpl.2018.00027
https://doi.org/10.1109/fpl.2018.00027
Autor:
Kevin Nealis, Debbie Marr, Aravind Dasu, Philip Colangelo, Eriko Nurvitadhi, Andrew Ling, Asit K. Mishra, Jeff Cook, Sergey Y. Shumarayev, Utku Aydonat, Davor Capalija
Publikováno v:
FPGA
FPGAs or ASICs? There is a long-running debate on this. FPGAs are extremely flexible while ASICs offer top efficiency but inflexible. We believe that FPGAs and ASICs are better together, to offer both flexible and efficient solutions. We propose sing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9a795ba489026080ad67bbecf1469e37
https://doi.org/10.1145/3174243.3174966
https://doi.org/10.1145/3174243.3174966
Autor:
Chris N. Johnson, Suchit Subhaschandra, Srivatsan Krishnan, Eriko Nurvitadhi, Debbie Marr, Duncan J. M. Moss, Asit K. Mishra, Jaewoong Sim, Philip H. W. Leong, P. Ratuszniak
Publikováno v:
FPGA
General Matrix to Matrix multiplication (GEMM) is the cornerstone for a wide gamut of applications in high performance computing (HPC), scientific computing (SC) and more recently, deep learning. In this work, we present a customizable matrix multipl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dc5d6edd0a40449cc1d00a2242a4642b
https://doi.org/10.1145/3174243.3174258
https://doi.org/10.1145/3174243.3174258
Autor:
Srivatsan Krishnan, Eriko Nurvitadhi, Suchit Subhaschandra, Yinger Jack Z, Duncan J. M. Moss, Andrew Ling, Debbie Marr, Davor Capalija
Publikováno v:
FPT
Deep neural networks (DNNs) have gained popularity for their state-of-the-art accuracy and relative ease of use. DNNs rely on a growing variety of matrix multiply operations (i.e., dense to sparse, FP32 to N-bit). We propose an OpenCL-based matrix mu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::49dffe5f846ddbf75c3a94500ae7471a
https://doi.org/10.1109/fpt.2017.8280155
https://doi.org/10.1109/fpt.2017.8280155
Autor:
Suchit Subhaschandra, Duncan J. M. Moss, Debbie Marr, Jaewoong Sim, Eriko Nurvitadhi, Asit K. Mishra, Philip H. W. Leong
Publikováno v:
FPL
Convolutional neural networks (CNNs) are deployed in a wide range of image recognition, scene segmentation and object detection applications. Achieving state of the art accuracy in CNNs often results in large models and complex topologies that requir
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8ce092824be5ea1fe35dbb26ce8d594e
https://doi.org/10.23919/fpl.2017.8056823
https://doi.org/10.23919/fpl.2017.8056823
Autor:
Eriko Nurvitadhi, Jaewoong Sim, Suchit Subhaschandra, Krishnan Srivatsan, Ganesh Venkatesh, Yeong Tat Liew, Debbie Marr, Duncan J. M. Moss, Randy Renfu Huang, Jason Ong Gee Hock, Guy Boudoukh
Publikováno v:
FPGA
Current-generation Deep Neural Networks (DNNs), such as AlexNet and VGG, rely heavily on dense floating-point matrix multiplication (GEMM), which maps well to GPUs (regular parallelism, high TFLOP/s). Because of this, GPUs are widely used for acceler
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2c1b38fb3f3e8c4ba896caf728db4ec1
https://doi.org/10.1145/3020078.3021740
https://doi.org/10.1145/3020078.3021740