Cut Your Data Center Costs by 90% While Processing Analytics 20X Faster
What You'll Learn in This White Paper:
1. Why Traditional Hardware Can't Keep Up With Data Growth
Discover why Moore's Law no longer applies to analytics workloads, and why CPUs and GPUs fall short when processing modern data-intensive workloads at scale.
2. The Architecture Behind 20X Performance Gains
Learn how Speedata's Coarse-Grained Reconfigurable Architecture (CGRA) overcomes branch divergence, handles diverse data types, and processes billions of rows in parallel, achieving 20X average speedup over vanilla Spark.
3. How Domain-Specific Accelerators Transform Analytics
Understand the three critical requirements for analytics acceleration - massive parallelism, branch handling, and support for variable-length data types like strings and timestamps.
4. Accelerated Parquet Processing at the Hardware Level
See how the APU decompresses, decodes, and processes columnar data formats in a single streamlined pipeline, eliminating memory bottlenecks that plague CPU and GPU architectures.
5. Seamless Integration Into Your Existing Spark Environment
Explore how Speedata transparently plugs into Apache Spark's Catalyst optimizer with zero code changes, delivering dramatic acceleration across Kubernetes, YARN, and standalone deployments.
