The company's DeepSparse software is able to use only the host processor, an x86 chip from Intel, AMD or, in future, ARM-based chips, without any assistance from the Nvidia GPUs.Īlso: AMD vs Intel: Which desktop processor is right for you? Returning inference contender Neural Magic, a venture-backed startup co-founded by Nir Shavit, a scholar at MIT, once again brought to bear its special software that can find which "neural weights" of a neural network can be left unused so they are not processed by the computer chip, thus saving on computing demands. New participants included Paris-based cTuning, a non-profit that is developing open-source tools for AI programmers to reproduce benchmark test results across different hardware platforms.Īlso: In latest benchmark test of AI, it's mostly Nvidia competing against NvidiaĬTuning took the top spot for the lowest latency, the shortest time from submission of a query to when the answer comes back, for four out of five tasks on the benchmark for edge computing, within the closed category.
MLCommons said that "a record-breaking 25 submitting organizations" submitted "over 6,700 performance results, and more than 2,400 performance and power efficiency measurements." That is up from 5,300 performance measurements and 2,400 power measurements in September. The results showed more organizations buying into the benchmark tests. A spreadsheet lists the results for all the different segments of data center and edge. The reported results pertain to computer systems operating in data centers and the "edge," a term that has come to encompass a variety of computer systems other than traditional data center machines. Also: Neural Magic's sparsity, Nvidia's Hopper, and Alibaba's network among firsts in latest MLPerf AI benchmarksįor the benchmarks, chip and system makers compete to see how well they can do on measures such as the number of photos processed in a single second, or how low they can get latency, the total round-trip time for a request to be sent to the computer and a prediction to be returned.
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