Using Raspberry Pi GPU for DNN
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Transcript of Using Raspberry Pi GPU for DNN
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rotate(broadcast, r1, 0)fmul(r3, r4, r5)fadd(ra0, ra0, r3)rotate(broadcast, r1, 1)fmul(r3, r4, r5)fadd(ra1, ra1, r3)rotate(broadcast, r1, 2)fmul(r3, r4, r5)fadd(ra1, ra1, r3)
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rotate(broadcast, r1, 0)fmul(r3, r4, r5)fadd(ra0, ra0, r3)rotate(broadcast, r1, 1)fmul(r3, r4, r5)fadd(ra1, ra1, r3)rotate(broadcast, r1, 2)fmul(r3, r4, r5)fadd(ra1, ra1, r3)
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rotate(broadcast, r1, 0)fmul(r3, r4, r5)rotate(broadcast, r1, 1)fadd(ra0, ra0, r3).fmul(r3, r4, r5)rotate(broadcast, r1, 2)fadd(ra1, ra1, r3).fmul(r3, r4, r5)rotate(broadcast, r1, 3)fadd(ra2, ra2, r3).fmul(r3, r4, r5)rotate(broadcast, r1, 4)
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rotate(broadcast, r1, -13)fadd(rb[14], rb[14], r3).fmul(r3, r4, r5)rotate(broadcast, r1, -14)fadd(ra[14], ra[14], r3).fmul(r3, r4, r5)iadd(null, element_number, -15, set_flags=True).rotate(broadcast, r1, -15)isub(r2, r2, 1, cond='zs')jzc(L.loop)
rotate(broadcast, r1, -13)fadd(rb[14], rb[14], r3).fmul(r3, r4, r5)rotate(broadcast, r1, -14)fadd(ra[14], ra[14], r3).fmul(r3, r4, r5)iadd(null, element_number, -15, set_flags=True).rotate(broadcast, r1, -15)isub(r2, r2, 1, cond='zs')jzc(L.loop)
rotate(broadcast, r1, -13)fadd(rb[14], rb[14], r3).fmul(r3, r4, r5)rotate(broadcast, r1, -14)fadd(ra[14], ra[14], r3).fmul(r3, r4, r5)iadd(null, element_number, -15, set_flags=True).rotate(broadcast, r1, -15)isub(r2, r2, 1, cond='zs')jzc(L.loop)
rotate(broadcast, r1, -13)fadd(rb[14], rb[14], r3).fmul(r3, r4, r5)iadd(null, element_number, -14, set_flags=True).rotate(broadcast, r1, -14)fadd(ra[14], ra[14], r3, set_flags=False).fmul(r3, r4, r5)iadd(r2, r2, -1, cond='zs').rotate(broadcast, r1, -15)jzc(L.loop)
rotate(broadcast, r1, -13)fadd(rb[14], rb[14], r3).fmul(r3, r4, r5)rotate(broadcast, r1, -14)fadd(ra[14], ra[14], r3).fmul(r3, r4, r5)iadd(null, element_number, -15, set_flags=True).rotate(broadcast, r1, -15)isub(r2, r2, 1, cond='zs')jzc(L.loop)
rotate(broadcast, r1, -13)fadd(rb[14], rb[14], r3).fmul(r3, r4, r5)iadd(null, element_number, -14, set_flags=True).rotate(broadcast, r1, -14)fadd(ra[14], ra[14], r3, set_flags=False).fmul(r3, r4, r5)iadd(r2, r2, -1, cond='zs').rotate(broadcast, r1, -15)jzc(L.loop)
rotate(broadcast, r1, -13)fadd(rb[14], rb[14], r3).fmul(r3, r4, r5)rotate(broadcast, r1, -14)fadd(ra[14], ra[14], r3).fmul(r3, r4, r5)iadd(null, element_number, -15, set_flags=True).rotate(broadcast, r1, -15)isub(r2, r2, 1, cond='zs')jzc(L.loop)
iadd(null, element_number, -13, set_flags=True).rotate(broadcast, r1, -13)fadd(rb[14], rb[14], r3, set_flags=False).fmul(r3, r4, r5)isub(r2, r2, -14, cond='zs', set_flags=False).rotate(broadcast, r1, -14)fadd(ra[14], ra[14], r3, set_flags=False).fmul(r3, r4, r5)iadd(r2, r2, -15, cond='zs').rotate(broadcast, r1, -15)jzc(L.loop)
rotate(broadcast, r1, -13)fadd(rb[14], rb[14], r3).fmul(r3, r4, r5)rotate(broadcast, r1, -14)fadd(ra[14], ra[14], r3).fmul(r3, r4, r5)iadd(null, element_number, -15, set_flags=True).rotate(broadcast, r1, -15)isub(r2, r2, 1, cond='zs')jzc(L.loop)
iadd(null, element_number, -13, set_flags=True).rotate(broadcast, r1, -13)fadd(rb[14], rb[14], r3, set_flags=False).fmul(r3, r4, r5)isub(r2, r2, -14, cond='zs', set_flags=False).rotate(broadcast, r1, -14)fadd(ra[14], ra[14], r3, set_flags=False).fmul(r3, r4, r5)iadd(r2, r2, -15, cond='zs').rotate(broadcast, r1, -15)jzc(L.loop)
rotate(broadcast, r1, -13)fadd(rb[14], rb[14], r3).fmul(r3, r4, r5)rotate(broadcast, r1, -14)fadd(ra[14], ra[14], r3).fmul(r3, r4, r5)iadd(null, element_number, -15, set_flags=True).rotate(broadcast, r1, -15)isub(r2, r2, 1, cond='zs')jzc(L.loop)
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1 99.58% cicada, cicala 2 0.19% cockroach, roach 3 0.06% cricket 4 0.05% grasshopper, hopper 5 0.04% leafhopper 6 0.02% lacewing, lacewing fly 7 0.01% barn spider, Araneus cavaticus 8 0.00% ground beetle, carabid beetle 9 0.00% isopod 10 0.00% mantis, mantid
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![Analysis of Large-Scale Multi-Tenant GPU Clusters for DNN ... · Similar to clusters setup for big data analysis [12,50], using shared clusters can facilitate better utilization and](https://static.fdocuments.net/doc/165x107/5ec5caefdfe04557bd2f236c/analysis-of-large-scale-multi-tenant-gpu-clusters-for-dnn-similar-to-clusters.jpg)
