![]() Nvidia is already trading at more than double the value of its large-cap semiconductor peers. We conducted some rough comparisons for Nvidia's stock, which are shown in the table below. Perhaps a few years of near monopoly could change that, but currently, there doesn't seem to be anything on the horizon.Ĭonsidering Nvidia's software as their true competitive advantage, should they be viewed as a software company? This idea may seem mildly outlandish but is worth considering. While there are software libraries attempting to displace Nvidia, these are owned or largely supported by software companies that don't care enough about the intricacies GPU firmware intricacies to create a true alternative. Although not an operating system per se, CUDA's ubiquity and relative ease of use have made it the de facto common software layer for AI software meeting silicon.Ī big part of the disconnect right now is that for the first time Nvidia's strong market position is based on software more than its hardware.ĪMD has never had anything to rival CUDA, and from what we can tell they are not even trying. Nvidia has maintained its lead thanks to its CUDA software. Nvidia emerged as the winner in most of those contests, but there was always some competition to challenge them. For years, the company had to compete with AMD for leadership in the GPU Feeds and Speeds race. There are currently no signs of a downturn, but, to put it politely, Nvidia sometimes struggles to accurately forecast its end markets and effectively communicate its expectations to the market.Ī big part of the disconnect right now is that for the first time Nvidia's strong market position is based on software more than its hardware. Although their CEO has done an incredible job in bringing them to this point, combining deep technical understanding, a keen strategic mind, and eloquence to convince others of their vision, the Street has often become overexcited about their numbers, often just before a major inventory correction. While Nvidia is unquestionably the leader in the hottest new market, and there are no signs of anyone challenging their dominance, it's important to note that the company has experienced boom/bust swings throughout its 40-year history. Jonathan has developed growth strategies and alliances for companies in the mobile, networking, gaming, and software industries. Guest author Jonathan Goldberg is the founder of D2D Advisory, a multi-functional consulting firm. These are significant multiples that may give many investors pause. The company is strategically well-positioned, which is reflected in its stock price, currently trading at 167x trailing twelve months earnings and 67 times this year's estimated EPS. Nvidia has largely captured all the market for chips used for training AI models and is also performing well with chips for inference. Setting aside what the latest AI models are actually good for, it is not surprising that investors are looking for stocks with "AI exposure." Unfortunately, this turns out to be a fairly short list at the moment, and at the top of that list is Nvidia. /apps/cuda/8.0/doc/pdf/CUDA_Quick_Start_Guide.The big picture: The world has gone mad for AI.Finally, run your CUDA-based code or binaries.ĭocumentation Home Page, User Guides, and Manuals Next, load the CUDA module as described above, and then start your specific CUDA tool(s): ~]$ module load apps/cuda/8.0ģ. To start an Interactive SRUN session, run the command below with example resources: ~]$ srun -time=02:00:00 -nodes=1 -cpus-per-task=4 -gres=gpu:1 -pty ~]$Ģ. To run CUDA tools, the following steps must be taken, in addition to using another command sequence.ġ. Note: All CUDA jobs should be run in an SBATCH/SRUN session on the cuda partition, and NOT on the login nodes!. ![]() For help on submitting jobs to the queue, see our SLURM User’s Guide. Your SLURM executables, tools, and options may vary from the example below.
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