Katydid

62 ms·

1. 571.▲
   Intel's Knights Landing Processor Can Stand on Its Own--But Probably Won't(nextplatform.com)

   3 points by Katydid 9y ago|0 comments
2. 572.▲
   by Katydid 9y ago

   Wouldn't say it's that simple. The biggest supercomputers need to have a balance between fat-ass manycore for the MPI/numerics (which won't go away until physics problems can be solved by DL--seems unlikely); GPUs for tr
3. 573.▲
   The Biggest Shift in Supercomputing Since GPU Acceleration(nextplatform.com)

   3 points by Katydid 9y ago|2 comments
4. 574.▲
   Competition Returns to X86 Servers in Epyc Fashion(nextplatform.com)

   4 points by Katydid 9y ago|0 comments
5. 575.▲
   Intel's Knights Landing Can Stand Alone–But Often Won’t(nextplatform.com)

   3 points by Katydid 9y ago|0 comments
6. 576.▲
   Top 500 Supercomputer Rankings: HPC Poised for Big Changes(nextplatform.com)

   4 points by Katydid 9y ago|0 comments
7. 577.▲
   Stencil Computations for Multi-Core Architectures Based on Machine Learning(sciencedirect.com)

   1 points by Katydid 9y ago|0 comments
8. 578.▲
   Computing at scale: From laptop to cloud and HPC(scholarworks.iu.edu)

   3 points by Katydid 9y ago|0 comments
9. 579.▲
   Serverless Computing: Current Trends and Open Problems(arxiv.org)

   5 points by Katydid 9y ago|0 comments
10. 580.▲
    Flash Drive Lifespan* Is* a Problem [pdf](cs.technion.ac.il)

    2 points by Katydid 9y ago|0 comments
11. 581.▲
    Selecting Optimized Datacenter for Recourse Allocation in Geo-Distributed Clouds [pdf](eleconf.ir)

    3 points by Katydid 9y ago|0 comments
12. 582.▲
    Performance Isolation Anomalies in RDMA [pdf](mosharaf.com)

    2 points by Katydid 9y ago|0 comments
13. 583.▲
    How to Measure the Killer Microsecond [pdf](infoscience.epfl.ch)

    1 points by Katydid 9y ago|0 comments
14. 584.▲
    When No One Can Make Money in Systems(nextplatform.com)

    2 points by Katydid 9y ago|0 comments
15. 585.▲
    Python Coils Around FPGAs for Broader Accelerator Reach(nextplatform.com)

    4 points by Katydid 9y ago|0 comments
16. 586.▲
    FPGA Startup Gathers Funding Force for Merged Hyperscale Inference(nextplatform.com)

    4 points by Katydid 9y ago|0 comments
17. 587.▲
    Memory-Like Storage Means File Systems Must Change(nextplatform.com)

    52 points by Katydid 9y ago|9 comments
18. 588.▲
    An effective algorithm for hyperparameter optimization of neural networks [pdf](arxiv.org)

    1 points by Katydid 9y ago|0 comments
19. 589.▲
    Selective Classification for Deep Neural Networks(arxiv.org)

    3 points by Katydid 9y ago|0 comments
20. 590.▲
    Energy-Proportional Systems: A New Definition [pdf](research.cs.wisc.edu)

    1 points by Katydid 9y ago|0 comments
21. 591.▲
    Jenga: Sotware-Defined Cache Hierarchies [pdf](people.csail.mit.edu)

    24 points by Katydid 9y ago|3 comments
22. 592.▲
    Bayesian Compression for Deep Learning(arxiv.org)

    3 points by Katydid 9y ago|0 comments
23. 593.▲
    Under the Hood of Google’s TPU2 Machine Learning Clusters(nextplatform.com)

    127 points by Katydid 9y ago|37 comments
24. 594.▲
    Neuromorphic Computing Based on Resistive RAM(delivery.acm.org)

    2 points by Katydid 9y ago|1 comments
25. 595.▲
    Application Development with Python for Heterogeneous Processor-Based FPGAs(arxiv.org)

    2 points by Katydid 9y ago|0 comments
26. 596.▲
    A Domain-Specific Language for Data Analytics Pipelines [pdf](iris.unito.it)

    2 points by Katydid 9y ago|0 comments
27. 597.▲
    Holography as deep learning(arxiv.org)

    3 points by Katydid 9y ago|0 comments
28. 598.▲
    Stanford FPGA Startup Gathers Funding Force for Merged Hyperscale Inference(nextplatform.com)

    4 points by Katydid 9y ago|0 comments
29. 599.▲
    Computation of K-Core Decomposition on Giraph [pdf](arxiv.org)

    2 points by Katydid 9y ago|0 comments
30. 600.▲
    Data Management Challenges in Production Machine Learning(delivery.acm.org)

    2 points by Katydid 9y ago|0 comments