An ARM Backend for PyPyls Tracing JIT - STUPS Group

40 8 EVALUATIONBenchmark cpython [ms] nojit, boehm [ms] jit, boehm [ms]ai 5931.82 ± 7.15 18630.77 ± 58.60 13316.69 ± 492.45bm_mako 1976.47 ± 12.54 6045.01 ± 274.69 3080.70 ± 234.98chaos 6548.26 ± 19.39 16049.27 ± 67.81 4100.33 ± 851.92crypto_pyaes 26746.72 ± 9.91 127704.81 ± 53.35 12099.35 ± 1280.47django 13111.72 ± 264.58 27510.31 ± 605.54 6240.66 ± 222.82fannkuch 17592.60 ± 65.52 61427.77 ± 1056.54 18752.91 ± 240.71float 8642.43 ± 129.71 16318.45 ± 335.48 4527.81 ± 293.27go 11457.86 ± 38.30 67172.65 ± 60.21 11438.12 ± 801.13html5lib 177656.38 ± 785.98 660478.63 ± 58354.54 339913.73 ± 15962.25meteor-contest 3758.29 ± 4.33 10932.99 ± 70.55 8207.28 ± 222.83nbody_modified 7533.80 ± 52.81 11473.04 ± 61.70 7840.77 ± 109.42raytrace-simple 33938.57 ± 528.15 77114.42 ± 960.34 17280.65 ± 414.07richards 3712.72 ± 14.59 10840.95 ± 93.97 1187.04 ± 118.55slowspitfire 6378.05 ± 1.84 25646.74 ± 1234.26 21371.59 ± 8929.30spectral-norm 6990.59 ± 30.40 28566.51 ± 25.40 4492.29 ± 171.88spitfire_cstringio 153292.00 ± 125.83 257690.40 ± 636.23 189844.20 ± 979.49telco 15434.80 ± 9.53 61941.56 ± 49.16 10938.12 ± 219.95twisted_iteration 2055.69 ± 4.71 7319.68 ± 86.70 1305.72 ± 149.00twisted_names 139.98 ± 0.98 362.43 ± 6.55 385.62 ± 138.98twisted_pb 1076.19 ± 66.42 3400.00 ± 471.40 4066.67 ± 1394.84twisted_tcp 13386.24 ± 81.21 43825.39 ± 3205.68 33173.15 ± 4922.12waf 77516.19 ± 3944.68 80218.64 ± 8958.83 77198.68 ± 6029.46Table 1: Absolute runtimes for standard PyPy benchmarks run on ARMarchitectural differences. For some benchmarks, such as the float benchmark, the ARMbackend is currently slower than the x86 backend because on ARM the JIT does not yetsupport optimized floating point operations. On x86 the JIT in combination the PyPy’sown GCs perform significantly better than using Boehm. Given the similar results onboth platforms using the Boehm GC, it is to be expected to see speedups comparable tothose on x86 once PyPy’s GCs are integrated on ARM.