White Paper: Smashing Big Data Costs with GZIP Hardware. Abstract. Juan D. Deaton, Ph.D. Research and Development

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1 White Paper: Smashing Big Data Costs with GZIP Hardware Juan D. Deaton, Ph.D. Research and Development Adam Bacon Sales Abstract GZIP data compression hardware has a critical role of increasing performance and smashing the monstrous costs of energy in big data systems. To demonstrate the benefits of using GZIP hardware, AHA assembled a web server experiment to compare the performance of serving pages using: No GZIP CPU performing GZIP AHA372 Hardware Accelerators for GZIP Using effective throughput, CPU utilization, and energy efficiency, these were some key results from the experiment: When the CPU simultaneously serves pages and performs GZIP, it consumes 5x more times energy and throughput drops by almost 5x. Hardware GZIP has a huge 18x throughput and 17x energy efficiency advantage over the CPU performing GZIP. With the energy costs of CPU GZIP, the break even point of GZIP hardware is between days. This paper shows that GZIP hardware offloading increases network I/O, optimizes workloads, and results in optimal system designs requiring significantly less capital and operational expenditures. Comtech EF Data Corporation 1126 Alturas Drive Moscow ID tel: fax: sales@aha.com

2 I Introduction Juan D. Deaton, James Purdy, Adam Bacon AHA Products Group Comtech EF Data 1126 Alturas Drive Moscow, ID Corresponding Authors: GZIP data compression has a critical role of increasing performance and smashing the monstrous costs of energy in big data systems. Using compressed data, systems require less energy and computing resources to store, transmit, and process data. Consequently, many applications have adopted GZIP compression such as web page servers, WAN optimization, financial trading systems, data storage, genomics, and even Hadoop. Unfortunately, some users don t use GZIP because CPUs can become heavily loaded resulting in decreased network performance and energy efficiency. Fortunately, GZIP hardware can offload data compression from CPUs and has the following benefits in big data systems: Increases System Performance GZIP hardware increases performance by removing Experiment CPU bottlenecks Setup and increasing network I/O. Reduces Operational Expenditures (OpEx) Huge energy cost savings from GZIP hardware creates a break even point on the order of weeks. Reduces Capital Expenditures (CapEx) Systems require fewer compute nodes since CPUs operate more efficiently. Integrates Plug and Play Our customers are surprised how easy our drop-in replacement for GZIP and ZLIB is. Through using GZIP hardware, CPU offloading increases network I/O, energy efficiency, and results in systems requiring OpEx and CapEx. To demonstrate the benefits of GZIP, AHA created a hardware offloading experiment using a web page server. A hardware configuration diagram of the experiment is shown in Figure Client Emulator Page Requests Apache Web Server Power Meter 10 Gig-E 120 VAC 120 Page Responses No GZIP CPU GZIP Hardware GZIP PowerEdge R720 Motherboard Watts up? PRO ES Intel Xeon E GHz (Total 8 cores) Accuracy: +/- 1.5% 24 X 4GB RDIMM, 1600MT/s RAM Western Digital WD800JD-75MSA2 Intel 82598EB 10-Gigabit AT2 Server Adapter 40 Gbps Compression: 2x AHA372 20Gbps GZIP Accelerators Supermicro X8DTL-6F Motherboard Intel Xeon E5620 CPU 3 X 2GB Kingston KVR13R9S8K3/6I Seagate Barracuda ST AS Intel 82598EB 10-Gigabit AT2 Server Adapter Client Emulator sends HTTP requests Fig. 1. GZIP hardware offloading on a web server: reduces OpEX, CapEx and increases system performance. - Requests maximize throughput of 10 G link AHA Products Group -1- Technical White Paper Webserver responds with GZIP d page

3 II GZIP Hardware Offloading Experiment In this experiment, the client emulator floods the Apache web server with page requests. To provide performance comparisons, the web server changes its page responses using no GZIP, CPU GZIP, and hardware GZIP. Hardware GZIP compression is provided with two AHA372 accelerators. Additionally, a power meter measures watts used by the system. Through this configuration, we demonstrate how GZIP compression affects bottle necks, optimizes workloads, and reduces operational and capital cost. A. Evaluation Metrics For performance comparisons, we a show a strip chart with rolling averages of the following metrics: Effective of the 10 Gig-E link of the Apache Web Server Joule/Gigabit Transmitted by the Apache Web Server The strip chart in Figure 2 shows these metrics captured in the bars labeled:, CPU Load, and using no GZIP, CPU GZIP, and AHA GZIP. Using this data we show the need for GZIP hardware and the performance increases from removing CPU bottle necks and increasing network I/O. No GZIP CPU GZIP GZIP 9 Gbps 15% 2 Gbps 100 % 35 Gbps 59% GZIP, the web server is able to respond to web pages at 9 Gbps. However, when compared to the CPU GZIP case, there is almost a 5x drop in throughput to 2 Gbps. Additionally, the 8 Core CPU is at 100% load and consumes 7x more energy. Thus, the CPU is inefficient at simultaneously serving pages and performing compression. In this case, GZIP is creating a CPU bottleneck, which requires offloading GZIP onto hardware. Fig. 3. No#GZIP 9 Gbps 15% 16 J/Gb CPU#GZIP 2 Gbps 100 % 116 J/Gb No GZIP vs. CPU GZIP: The CPU is inefficient when simultaneously serving pages and performing compression. B. GZIP Hardware Removes CPU Bottlenecks GZIP hardware excels at removing CPU bottlenecks. From Figure 4, there are huge increases in performance and energy efficiency over CPU performing GZIP. Hardware GZIP has a huge 18x throughput and 17x energy efficiency advantage over CPU GZIP. Even at full load with 8 cores, CPU GZIP is only capable of 6% of the throughput compared to the GZIP hardware case. Finally, there is still available CPU cycles for performing other tasks. CPU#GZIP GZIP 16 J/Gb 116 J/Gb 6.8 J/Gb 2 Gbps 35 Gbps Fig. 2. Effective,, and between no, CPU, and hardware compression scenarios: hardware GZIP shows the best throughput and energy efficiency. III Increasing System Performance A. CPUs are Inefficient at Performing GZIP To illustrate the need for GZIP hardware, notice the drop in throughput and increase in between the no GZIP and CPU GZIP cases. A focused comparison is shown in Figure 3. With no 100 % 116 J/Gb 59% 6.8 J/Gb Fig. 4. CPU GZIP vs. Hardware GZIP: Hardware GZIP removes the CPU bottle neck and has a huge 18x throughput and 17x energy efficiency advantage over CPU GZIP. AHA Products Group -2- Technical White Paper

4 C. GZIP Hardware Increases Network I/O In addition to removing CPU bottlenecks, GZIP hardware excels at increasing network I/O. Figure 5 shows over a 4x increase (from 9 Gbps to 35 Gbps) in throughput from the no GZIP case to the hardware GZIP case. Since our maximum link throughput is 10 Gbps, we reach the maximum effective data rate possible for the given compression ratio (10 Gbps Link * 3.5:1 Compression Ratio = 35 Gbps effective throughput). As shown in Figure 1, this experiment used two AHA372s for an aggregate input compression rate of 40 Gbps 1. However, the hardware GZIP case is limited to 35 Gbps because the data has a compression ratio on the order of 3.5:1. IV Reducing OpEx In addition to the performance benefits, GZIP hardware reduces OpEx by reducing the amount of energy consumed and can even pay for itself many times over. Using the data from this experiment, we can calculate when the cost for energy saved is equal to the cost of the GZIP hardware, which we call the energy break-even point (ebep). The ebep is shown in Figure 6 for a given cost of electricity and is calculated against the No GZIP and CPU GZIP cases. In areas where the cost of electricity is high (e.g., Japan, Australia, and Germany), compression hardware can easily pay for itself many times over in energy costs alone. No GZIP GZIP 9 Gbps 35 Gbps 15% 59% 16 J/Gb 6.8 J/Gb Fig. 6. Break Even Point for using GZIP hardware: Even without considering the performance benefits, hardware GZIP has a short break even point on energy alone, easily paying for itself many times over. Fig. 5. No GZIP vs. Hardware GZIP: Hardware GZIP shows 4x increase in throughput and more than 2x increase in energy efficiency while allowing the CPU to serve more pages. When adding compression to increase network I/O, knowing the compression ratio of data is important in order to select the compression rate of hardware for the application. In this experiment, we used two AHA372s for a maximum input compression rate of 40 Gbps and throughput limit of 35 Gbps, due to the compression ratio. If the data had a higher compression ratio, such as 6:1 or 8:1 we would require faster hardware, such as the AHA378, to reach the maximum effective data rate possible for those compression ratios (60 Gbps and 80 Gbps, respectively). V Reducing CapEx In addition to reducing OpEx, compression hardware reduces CapEx by creating equivalent performing systems using less hardware. We can determine the reduction in CapEx by revisiting how hardware GZIP removes CPU bottlenecks and increases network I/O. To show the CapEx reduction by removing CPU bottle necks, we revisit the comparison between CPU to hardware GZIP. In this comparison, we noted an 18x difference in throughput in Figure 4. For a performance match with GZIP hardware, 18 CPUs (i.e., compute nodes) would be required in the CPU GZIP case (18 CPU * 2 Gbps = 36 Gbps). We also note that further utilization optimizations are possible in hardware GZIP case, since the CPU is only at 59%. Theoretically, the addition of another 1 Alternatively, we could have used a single AHA374 for 40 Gbps. AHA Products Group -3- Technical White Paper

5 10Gig-E card and 80 Gbps AHA378 card could maximize CPU utilization and achieve a throughput of 70 Gbps. To show CapEx reduction in the increasing network I/O case, we revisit the comparison between the No GZIP case and the hardware GZIP in Figure 5. To exceed the throughput of hardware compression (35 Gbps), the No GZIP case requires replacing the 10Gig-E card with a 40Gig-E, resulting in a much higher CapEx for network hardware (i.e., network cards, cables and switches ). In a cost comparison, the CapEx of a single 40Gig-E switch alone can be the total cost of GZIP hardware for an entire network. With GZIP hardware offloading, systems with 10Gig-E infrastructure can achieve close to 40Gig-E speeds with the installation of much less expensive PCIe cards. VI Integrates Plug and Play While not illustrated in our experiment, integrating AHA GZIP hardware is plug and play. After installing the PCIe card, the entire driver installation procedure consists of five command line entries. Additionally, to support a drop in replacement of ZLIB functionality, AHA provides a ZLIB library replacement for the Linux ZLIB library. This ZLIB library replacement provides immediate integration of compression offload into existing applications. For expert users, complete source code for drivers and utilities are provided. If users have more complex applications, AHA also provides direct engineering support for integration. Based on our engineering support and hardware performance, our recent customers have said, Why isn t everyone using this? It s even easy to integrate this hardware into Hadoop, high frequency trading, storage, and genomics data applications. VII Summary and Conclusion GZIP compression hardware offloading is a clear winner, when it comes to energy cost reduction and performance improvement. Hardware compression creates more efficient network I/O, which optimizes workloads on computing systems. More efficient network I/O reduces energy costs. With optimized workloads, fewer computing nodes are required resulting in less capital and operating costs. GZIP hardware offloading increases system performance, reduces Opex/CapEx, and integrates plug and play. Although big data applications can consume a monstrous amount of resources, GZIP hardware increases performance and smashes costs. GZIP Hardware at a Glance AHA371/AHA372 Compression Decompression Accelerator A l t Card C d Algorithms: GZIP, ZLIB, LZS Low Profile PCIe 2.0x8 Compression Rate: AHA Gbps AHA Gbps AHA374/AHA378 Compression/ /Decompression Accelerator Card Algorithms GZIP, ZLIB, LZS Low Profile PCIe 3.0 AHA374 Single Slot AHA378 Dual Slot Compression Rates: AHA Gbps AHA Gbps 6 AHA Products Group -4- Technical White Paper

6 About AHA Products Group The AHA Products Group (AHA) of Comtech EF Data Corporation develops and markets applicationspecific integrated circuits (ASICs), boards, and intellectual property core technology for communications systems applications. Located in Moscow, Idaho, AHA has been providing leading edge Forward Error Correction and Lossless Data Compression technology for almost three decades. AHA offers a variety of standard and custom hardware solutions for the communications industry. Visit us at Comtech EF Data Corporation 1126 Alturas Drive Moscow ID tel: fax: sales@aha.com AHA Products Group -5- Technical White Paper