Speed Your Time to First Token (and Save!)
Speed Your Time to First Token (and Save!)
WEKA Delivers Dramatically Faster Time to First Token & Optimized Token Processing.
As model sizes and context window sizes expand, the demand for efficient and large-scale memory is increasing beyond the fixed amounts available today.
Optimizing token generation is the key to AI adoption, growth, and organizational success.
Don’t let hitting the memory bandwidth wall slow down your time to first token.↓
Don’t let hitting the memory wall:
- Limit the capabilities of AI application
- Erode engagement rates for end users due to slow prompt result
- Require unnecessarily expensive GPUs and infrastructure
Memory Myths
Inferencing is limited to the memory in a GPU
More memory requirements = more GPUs
WEKA Breaks
Through Memory Myths.
“Just as breaking the sound barrier unlocked new frontiers in aerospace innovation, WEKA’s Augmented Memory Grid is shattering the AI memory barrier, expanding GPU memory and optimizing token efficiency across the NVIDIA AI Data Platform.”
WEKA’s Augmented Memory Grid™ blasts through the memory wall optimizing inference infrastructure and supercharging token efficiency.
WEKA extends memory hierarchy to cache prefixes or key value (KV) pairs around three orders of magnitude (1000x) more than today s fixed DRAM increments of single terabytes.
WEKA Supercharges
Token Efficiency
Lower Latency
Latency is the key to optimizing token generation.
WEKA’s GPU-optimized architecture, featuring NVMe SSD acceleration and high-speed networking, enables token processing at microsecond latencies.
→ And no one, seriously no one, does ultra-low latency better than WEKA.
Prove it.
We put the WEKA® Data Platform to the test, leveraging NVIDIA Magnum IO GPUDirect Storage (GDS) and a highperformance 8-node WEKApod.
Our tests demonstrated a staggering 41x reduction in time to first token prefill time on LLaMA3.1-70B for 105K tokens, dropping from 23.97 seconds to just 0.58 seconds.
“By extending GPU memory and maximizing utilization across our Shakti Supercloud fleet, WEKA will help us deliver improved AI performance, faster inference, and better cost efficiency to our customers.”
Fewer GPUs
The secret to breaking through the wall of high-bandwidth memory limitations is to decouple GPU compute from memory.
For the very first time in the market, WEKA has made it possible to extend memory for inference workloads outside of the GPU.
→ No.It’s not a hole in the space time continuum.
It’s WEKA’s Augmented Memory Grid.
Explain how WEKA does it.
WEKA seamlessly extends GPU HBM beyond its current limitations. That’s right. We found ultra-low latency storage that functions like memory.
We treat microsecond latency NVMe storage and the GPUDirect RDMA as an adjacent tier of memory.
WEKA saves 24 seconds of compute time per request.
WEKA’s Augmented Memory Grid
makes it possible for GPUs to deliver 200% more capacity than they are currently delivering, so you can run your workloads with 30% fewer GPUs.
Reduced Costs
Every millisecond saved in token inference translates to reduced infrastructure overhead and efficiency gains.
WEKA enables optimized inference workloads so businesses can scale their AI applications cost- effectively while maintaining high levels of efficiency and accuracy.
Show me the money.
When you need fewer GPUs for the same workload, you can cut your AI inference costs by 30%.
WEKA’s Augmented Memory Grid
inferencing clusters can achieve higher cluster-wide output tokens, lowering the cost of token throughput by up to 24% for the entire inference system.
As enterprises scale their AI deployments, these optimizations
make LLMs and LRMs much more profitable, ensuring cost
efficiency without sacrificing accuracy or performance.
WEKA Focuses On Less.
Lower Latency. Fewer GPUs. Less Cost.
So Your AI Projects Can Do More.
MORE Tokens Faster.- MORE Customers Satisfied.
- MORE Revenue Realized.
With WEKA