GPU vs WSE

[𝗔𝗜] 𝗪𝗵𝗮𝘁 𝗽𝗲𝗼𝗽𝗹𝗲 𝘁𝗵𝗶𝗻𝗸 𝗮𝗯𝗼𝘂𝘁 𝗶𝗻𝗳𝗲𝗿𝗲𝗻𝗰𝗲 𝘀𝗽𝗲𝗲𝗱 𝗶𝘀:

• Faster chips just mean more raw compute
• Inference speed is mostly a software problem
• GPUs and TPUs are “good enough” for most workloads

𝗪𝗵𝗮𝘁 𝗶𝘁 𝘂𝘀𝘂𝗮𝗹𝗹𝘆 𝗶𝘀:

• The real bottleneck is 𝗱𝗮𝘁𝗮 𝗺𝗼𝘃𝗲𝗺𝗲𝗻𝘁, not arithmetic
• Model weights sitting off-chip create constant memory traffic
• Performance gains often come from keeping data closer to compute
• Cerebras’ 𝗪𝗮𝗳𝗲𝗿 𝗦𝗰𝗮𝗹𝗲 𝗘𝗻𝗴𝗶𝗻𝗲 reduces that movement by keeping 𝘄𝗲𝗶𝗴𝗵𝘁𝘀 𝗼𝗻-𝗰𝗵𝗶𝗽

𝗧𝗵𝗲 𝗴𝗮𝗽 𝗯𝗲𝘁𝘄𝗲𝗲𝗻 𝘁𝗵𝗲 𝘁𝘄𝗼 𝗶𝘀 𝗮 𝗵𝗮𝗿𝗱𝘄𝗮𝗿𝗲 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗮𝗹 𝗱𝗲𝘀𝗶𝗴𝗻.