Debunking the 100X GPU vs CPU Myth: An Evaluation of Throughput Computing on CPU and GPU Victor W. Lee, et al. Intel Corporation ISCA ’10 June 19-23, 2010, Saint-Malo, France

Intel vs. NVIDIA: Throughput Computing Smackdown! Victor W. Lee, et al. Intel Corporation ISCA ’10 June 19-23, 2010, Saint-Malo, France

Results Intel’s PaperPrevious Papers

Architecture Core i7 960GTX280

Hardware Core i processing elements 2-way hyper-threading 4-wide SIMD Caches 32KB/256KB/8MB out-of-order super-scalar GTX processing elements 100s hardware threads 8-wide SIMD* Caches 16KB/… texture sampling units transcendental units

Hardware

Bandwidth Bound Kernels SAXPY (scalar alpha x plus y) LBM (lattice Boltzmann method) SpMV (sparse matrix × vector) Low compute to memory ratio Optimizations: – Blocking reduces cache misses

Computation Bound Kernels SGEMM (sparse and dense) MC (Monte Carlo options) Conv (image convolution) FFT (fast Fourier transform) Bilat (bilateral filter) + GPU – Higher FLOPS – Hardware transcendentals + CPU: super-scalar

Gather/Scatter Bound Kernels GJK (collision detection) RC (ray casting) Irregular memory access + GPU: texture lookup + CPU: little need for SIMD

Synchronization Bound Kernels Hist (histogram) Solv (constraint solver) Atomic access to same memory + CPU: hardware atomic access Optimization: – Reduce synchronization…

Drama Courtesy of Prof. Harris

December 16, 2009 – One month after ISCA’s final papers were due. – The Federal Trade Commission filed an antitrust- related lawsuit against Intel Wednesday, accusing the chip maker of deliberately attempting hurt its competition and ultimately consumers. antitrust- related lawsuit against Intel Wednesday – The Federal Trade Commission's complaint against Intel for alleged anticompetitive practices has a new twist: graphics chips.Federal Trade Commission's complaint Antitrust

2009 was expensive for Intel The European Commission fined Intel for nearly 1.5 billion USD,European Commission fined Intel the US Federal Trade Commission sued Intel on anti-trust grounds, and US Federal Trade Commission sued Intel Intel settled with AMD for another 1.25 billion USD. Intel settled with AMD – If nothing else it was an expensive year, and while Intel settling with AMD was a significant milestone for the company it was not the end of their troubles.

Finally the settlement(s) The EU Fine is still under appeal ($1.45B) 8/4/2010 Intel Settles with the FCC Mother of All Programs: “…code name Intel bestowed on a series of payments it made to Dell…” – Intel: “Rebates” if you don’t use AMD

What is important about the context? The International Symposium on Computer Architecture (ISCA) in Saint-Malo, France, interestingly enough, is the same event where NVIDIA’s Chief Scientist Bill Dally received the prestigious 2010 Eckert-Mauchly Award for his pioneering work in architecture for parallel computing.2010 Eckert-Mauchly Award

NVIDIA Blog Response: “It’s a rare day in the world of technology when a company you compete with stands up at an important conference and declares that your technology is *only* up to 14 times faster than theirs.” “The real myth here is that multi-core CPUs are easy for any developer to use and see performance improvements.” only-up-to-14-times-faster-than-cpus-says-intel.html only-up-to-14-times-faster-than-cpus-says-intel.html

Undergraduate students learning parallel programming at M.I.T. disputed this when they looked at the performance increase they could get from different processor types and compared this with the amount of time they needed to spend in re-writing their code. According to them, for the same investment of time as coding for a CPU, they could get more than 35x the performance from a GPU.

Fermi cards were almost certainly unavailable when Intel commenced its project, but it's still worth noting that some of the GF100's architectural advances partially address (or at least alleviate) certain performance-limiting handicaps Intel points to when comparing Nehalem to a GT200 processor.

Can’t We All Get Along? Parallelization is hard, whether you're working with a quad-core x86 CPU or a 240-core GPU; each architecture has strengths and weaknesses that make it better or worse at handling certain kinds of workloads.